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The Bachelor of Arts in Multidisciplinary Studies (MDST)  is a multidisciplinary degree which allows students much flexibility in designing degree programs that relate to their personal academic and career goals. The MDST major permits an interdisciplinary approach to education allowing students the opportunity to acquire a well-rounded educational background and problem-solving skills. The objectives of the program are to develop students that have a solid foundation in the content material of three different disciplines and are skilled in communication, critical thinking, and analysis, investigating and solving problems, managing tasks, and relating to others. The program allows students to develop academic themes or topics that fall outside the usual disciplinary boundaries. The Bachelor of Arts in Multidisciplinary Studies is also available as an online degree program .

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• Volume 6, Issue 4
• Effectiveness of multidisciplinary team case management: difference-in-differences analysis
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• http://orcid.org/0000-0002-3266-1474 Jonathan Stokes 1 ,
• Søren Rud Kristensen 2 ,
• Kath Checkland 3 ,
• Peter Bower 1
• 1 NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre, Manchester Academic Health Science Centre, University of Manchester , Manchester , UK
• 2 Manchester Centre for Health Economics, University of Manchester , Manchester , UK
• 3 NIHR School for Primary Care Research, Centre for Primary Care, Manchester Academic Health Science Centre, University of Manchester , Manchester , UK
• Correspondence to Jonathan Stokes; jonathan.stokes-3{at}postgrad.manchester.ac.uk

Objectives To evaluate a multidisciplinary team (MDT) case management intervention, at the individual (direct effects of intervention) and practice levels (potential spillover effects).

Design Difference-in-differences design with multiple intervention start dates, analysing hospital admissions data. In secondary analyses, we stratified individual-level results by risk score.

Setting Single clinical commissioning group (CCG) in the UK's National Health Service (NHS).

Participants At the individual level, we matched 2049 intervention patients using propensity scoring one-to-one with control patients. At the practice level, 30 practices were compared using a natural experiment through staged implementation.

Intervention Practice Integrated Care Teams (PICTs), using MDT case management of high-risk patients together with a summary record of care versus usual care.

Direct and indirect outcome measures Primary measures of intervention effects were accident and emergency (A&E) visits; inpatient non-elective stays, 30-day re-admissions; inpatient elective stays; outpatient visits; and admissions for ambulatory care sensitive conditions. Secondary measures included inpatient length of stay; total cost of secondary care services; and patient satisfaction (at the practice level only).

Results At the individual level, we found slight, clinically trivial increases in inpatient non-elective admissions (+0.01 admissions per patient per month; 95% CI 0.00 to 0.01. Effect size (ES): 0.02) and 30-day re-admissions (+0.00; 0.00 to 0.01. ES: 0.03). We found no indication that highest risk patients benefitted more from the intervention. At the practice level, we found a small decrease in inpatient non-elective admissions (−0.63 admissions per 1000 patients per month; −1.17 to −0.09. ES: −0.24). However, this result did not withstand a robustness check; the estimate may have absorbed some differences in underlying practice trends.

Conclusions The intervention does not meet its primary aim, and the clinical significance and cost-effectiveness of these small practice-level effects is debatable. There is an ongoing need to develop effective ways to reduce unnecessary attendances in secondary care for the high-risk population.

• case management
• difference-in-differences
• integrated care
• multidisciplinary team

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

https://doi.org/10.1136/bmjopen-2015-010468

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Strengths and limitations of this study

This study addresses a number of shortcomings found in related literature from a recent systematic review.

The difference-in-differences methods can provide a rigorous assessment under certain conditions while evaluating an intervention in a real-world setting.

Results are analysed and presented at two levels to show direct effects of the intervention, as well as wider spillover effects of integrated care.

At the practice level, there may be some selection bias due to voluntary recruitment, although we predict this to be minimal based on our robustness checks.

At the individual level, results may be prone to some bias in favour of control participants due to the ongoing recruitment strategy versus a single time point propensity matching. Again, we predict this to be minimal, as participants and controls were well matched at the first start date.

Introduction

An ageing population with increasing number of long-term conditions (LTCs) and complex multimorbidity 1 , 2 has caused policymakers to rethink delivery of care. 3

There is increasing focus on the benefits of ‘integrated care’, to enable a more efficient and effective response to LTCs. 3 , 4 There is no consensus definition of what constitutes ‘integrated care’, 5 and the concept describes many different changes to the health system that can occur at multiple levels. 6 , 7 , 8 Practical implementation examples of integrated care include pooling of funds, joint commissioning, colocation of services, shared clinical records, and at the interface of the health system with the patient (ie, service delivery level) multidisciplinary team (MDT) working and case management. 7 , 8

In the UK's National Health Service (NHS), a common model of integrated care is the use of ‘multi-disciplinary team (MDT) case management of high-risk patients’. 9 , 10

We undertook a systematic review of this model of integrated care and found few effects across a number of relevant outcomes, barring a small effect on patient satisfaction, and short-term changes in self-reported health status. 6

We also identified gaps in the current literature. In the review, 78% of included studies were randomised controlled trials (RCTs). 6 We suggested a complementary role for rigorous quasi-experiments in routine settings to better balance internal and external validity. 11 , 12

The majority of studies also measured only direct (individual-level) effects. MDT case management used to manage a subset of patients could lead to broader changes, such as better ‘professional integration’ through team working. 13 , 14 These broader changes could lead to effects on the wider patient population, beyond those patients specifically managed by the MDT (what we call ‘spillover effects’).

Our contribution to the evidence base for MDT case management thus involved an evaluation of a local integrated care intervention using a robust quasi-experimental study design. We model effects using two distinct analyses: (1) individual-level analysis (to capture direct effects of the intervention) and (2) practice-level analysis (to capture any potential spillover effects).

The intervention

In Central Manchester, the MDT case management is achieved through Practice Integrated Care Teams (PICTs) introduced by the clinical commissioning group (CCG). PICTs conduct case finding, assess the needs of the individual identified, prepare individualised care plans, co-ordinate care and conduct regular review, monitoring and adaptation of the care plan. 15 The aim of the intervention was to reduce unnecessary attendances in secondary care for the high-risk population. 16

Table 1 gives an overview of the key aspects of the intervention. Compared with our previous systematic review of similar interventions, it is fairly common, where we identified the majority (58%) employing MDT case management (as opposed to a single case manager), and a predictive risk model as the primary method of identifying suitable patients. 6 Less commonly, this intervention took place in a system ranked as delivering ‘high’ strength of primary care (ie, strength of primary healthcare orientation of the health system as classified by Starfield and Shi 17 —the majority in the review came from a ‘low’-strength system, eg, USA: 64%). Additionally, the PICT intervention included involvement of a social worker (33% of studies involved a social worker in our previous review), providing further potential for ‘horizontal integration’ (ie, integration between separate organisations at the same level of the health system). 3

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Overview of intervention

Our study used a quasi-experimental pre–post design with a suitable control group to examine any change in outcomes induced by a policy change intervention—an adapted version of difference-in-differences (DD) analysis. 18

We prepared and analysed data at two distinct levels, each described separately below. Owing to a data governance issue at the CCG, intervention patients could not be identified at the individual level until nearly all practices implemented the intervention (patients were not consented prior to this date, so those joining before could not be included in the analysis—they were also excluded from our control group, so no contamination occurred). Figure 1 summarises the period of analysis for the individual and practice levels, showing the analysis and ‘pretrend’ period (ie, period prior to any practice/individual joining the intervention group) for each.

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Timeline of analyses highlighting key dates of practices and individual patients included in analysis joining the intervention.

With the PICT intervention having no single start date, we adapted our analysis to allow for this staged introduction (using a time fixed effect instead of the usual binary post dummy—see equations in practice level and individual level sections in the online supplementary material appendices). 18 , 19 The main difference from the standard DD approach is that the intervention and control groups are not static over time, allowing intervention patients/practices to join gradually over the monthly panel datasets, and comparing appropriately at each time point. This method has been used previously in the literature, 19 , 20 and we have adapted it to suit data at both of our levels of analyses (explained below, and in more detail in the online supplementary material appendices).

Supplemental material

We analysed anonymised data held by the CCG, from the ‘admitted patient care commissioning dataset’, submitted by all providers in England via the Secondary Uses Service (SUS). The dataset included all patient contacts with secondary care services, demographic data, as well as costs calculated through the national payment by results (PbR, together with local prices for local providers where applicable). For the analysis of pseudonymised/anonymised data, no formal ethics process was deemed necessary. The CCG had themselves previously consented the intervention individuals for use of their data for evaluation purposes. For patient satisfaction at the practice level, we used data from the GP Patient Survey (GPPS—see online supplementary material appendices).

Data preparation and analysis

All data preparation and analysis was carried out using STATA (V.13) (StataCorp. Stata Statistical Software: Release 13 . College Station, TX: StataCorp LP., 2013). The DD analysis estimate is unbiased only under the key assumption that the average difference between intervention and control units' trends would be the same in the absence of ‘treatment’ (ie, the PICT intervention). 18 This ‘parallel trends’ assumption is key to DD analysis and was tested graphically and statistically for each outcome assessed, at each analysis level (see online supplementary material appendices for graphs).

We analysed data distinctly at two levels:

Individual level: primary analysis

At the individual level, to obtain parallel pretrends, it was necessary to propensity match intervention patients to controls from within the same CCG (we matched on the characteristics for which the patients were recruited in practice to maximise comparability—see online supplementary material appendices for details). We then analysed 2049 intervention patients versus 2049 matched controls using the best-fitting count model for each outcome. 21 Outcome measures were summed to a count per patient per month over the period September 2010–March 2015 inclusive, to allow a 3-year pretrend period.

In all models, we adjusted for relevant individual covariates from the directed acyclic graph (DAG—see online supplementary material appendices), 22 as well as practice fixed effects (to control for any effects caused by characteristics of a specific practice rather than the intervention itself). 23 We cluster our SEs by practice to deal with concerns of serial correlation. 24 We took the average partial effect of results (for β 2 — see online supplementary material appendices for equation) and report these below (ie, the covariates adjusted absolute change in counts per patient per month). We additionally report the effect size (ES; standardised mean difference) as a measure of practical significance of each result. 25 We adopted Cohen's rule of thumb for interpreting ESs, that is, 0.2 indicates a small effect, 0.5 a medium and 0.8 a large effect. 26

Stratification by risk score

Patients were recruited to the intervention via risk tool score and clinical judgement. To test whether the highest risk patients (according to risk tool score) benefitted more from the PICT intervention than those with lower calculated risks also treated, we generated a ‘high-risk’ dummy. We reran the individual-level analysis with a difference-in-difference-in-differences (DDD) analysis, using an additional interaction term to determine subgroup effects (see online supplementary material appendices for equation).

2. Practice level: secondary analysis of spillover effects

At the practice level, practices gradually took up the intervention over a period of 18 months. At each time point (updating monthly in our dataset), the time fixed effects compare all intervention practices with all ‘controls’ (ie, all those practices that have not yet adopted the intervention, even though they will later adopt the intervention). 19 , 20 Outcomes were summed to a count per 1000 patients per month for each of the practices and analysed over the period September 2010–March 2015 inclusive, to overlap with the individual-level analysis.

We used a linear regression model, adjusting for fixed effects for each practice and time period (monthly—see online supplementary material appendices for equation). We cluster our SEs by practice to deal with concerns of serial correlation. 24

Outcome measures

Primary outcome measures for both analyses included:

Inpatient non-elective admissions

Re-admissions (30 days)

Inpatient elective admissions

Accident and emergency (A&E) visits

Outpatient visits

Admissions for ambulatory care sensitive conditions (ACSCs, which we used as a measure of patient safety in a health system with universal health coverage—see online supplementary material appendices for details)

Secondary outcome measures included:

Total cost of secondary care services (£)

Length of stay (inpatient)

Patient satisfaction (practice level only: measured through the GPPS—see online supplementary material appendices)

General satisfaction

LTC-specific satisfaction

Robustness check

At both levels of analysis, we additionally added a robustness check including a practice-specific time trend. This allows intervention and control practices to follow different trends and can help reveal any indication of the observed effect having absorbed any differences in underlying practice time trends. 18

At the practice level only, due to the voluntary roll-out of the intervention, we attempted to assess the effects of selection bias using a logistic regression model (including % males; % over 65; practice list size; number of general practitioners (GPs) per thousand patients; total Index of Multiple Deprivation (IMD) score 2010; and total % Quality and Outcomes Framework (QOF) achievement score). 27 We additionally reran the practice-level analysis excluding those practices recruited to the intervention in wave 1, assuming these to be the practices at most risk of selection bias if it did indeed occur. 19

Individual-level analysis

Sample characteristics.

A total of 2049 intervention patients were propensity score matched to non-intervention patients from the same CCG. As expected, the differences were small between matched patient baseline characteristics (see table 2 ).

Individual baseline characteristics (before and after matching)

Table 3 shows the crude absolute differences in mean outcome measures (PICT patients vs matched controls). As for the DD results in the section below, a negative estimate indicates a relative decrease in admissions for PICT patients compared with controls (ie, a negative intervention effect favours the intervention).

Average absolute outcomes per patient per month by PICT, preintervention/postintervention

DD parallel pretrends

We identified evidence of a significant difference between pretrends for outpatient visits at the individual level. This variable was potentially biased towards a result favouring the PICT intervention over controls. However, we found no statistically significant result favouring either group. All other variables satisfied the parallel trends assumption, with no indication of bias.

Table 4 shows the DD analysis results at the individual level. After adjustment for age, cumulative multimorbidity, IMD domains (excluding health) and practice and time fixed effects, we found a slight increase in inpatient non-elective admissions (0.0053 per patient per month; 95% CI 0.0004 to 0.0102) and 30-day inpatient readmissions (0.0041; 0.0018 to 0.0064). The ESs (0.02 and 0.03) were small. 26

Individual-level adjusted model results

All of the estimates withstood the addition of a practice-specific time trend.

We observed no relationship between risk score and time of recruitment into the intervention. Observing the plots of risk score versus total postintervention admissions, however, we see that there does appear to be a relationship between a higher risk score and increased non-elective admissions, A&E visits, total cost of secondary care services, admissions for ACSCs, inpatient length of stay and inpatient 30-day readmissions (see online supplementary material appendices). This implies that the risk score is a good predictor of these future admission types, as expected.

Results of the DDD analysis, however, indicate that those patients with a higher risk score did not benefit more from the intervention, and instead showed statistically significant increased inpatient non-elective admissions (0.0208 per patient per month; 95% CI 0.0083 to 0.0333. ES: 0.09), A&E visits (0.0363; 0.0128 to 0.0598. ES: 0.09) and inpatient length of stay (0.3071; 0.0592 to 0.5549. ES: 0.06—see online supplementary material appendices for full list of DDD estimates) compared with others. Again, the ESs indicate these increases were slight.

Practice-level analysis

Table 5 shows the practice characteristics of the intervention and control practices included in the analysis (comparing the practices which joined the intervention in wave 1 with those that joined the intervention at a later date). On average, the practices are very similar, with wave 1 practices with a slightly higher proportion of older patients, and a slightly more even male/female split.

Practice characteristics (wave 1 compared to later joining practices)

Table 6 shows the crude absolute differences in mean outcome measures (per 1000 patients per month) observed between the wave 1 PICT practices and those practices joining at a later date (shown as ‘controls’ for illustration purposes), preintervention and postintervention. As for the DD results in the section below, a negative estimate indicates a relative decrease in admissions for PICT practices compared with controls. For satisfaction outcomes, a positive estimate indicates increased satisfaction for the intervention practices compared to usual care.

Average absolute outcomes per 1000 patients per month by PICT (wave 1 compared to practices joining the intervention at a later date), preintervention/postintervention

We identified no significant differences between pretrends for any outcome at the practice level. These data satisfy the parallel trends assumption, with no indication of bias.

Table 7 shows the DD analysis results at the practice level. After adjustment for practice and time fixed effects, the difference for inpatient non-elective admissions was significant, with an estimated −0.63 admissions per 1000 patients per month (95% CI −1.17 to −0.09) for PICT practices compared with control practices.

Practice-level adjusted model results

The practical significance, as evidenced by the ES of −0.24, suggests a small effect of PICT on inpatient non-elective admissions at the practice level.

Following our robustness check, including a practice-specific time trend, the estimate for inpatient non-electives was no longer significant: −0.52 (−1.05 to 0.01. ES: −0.20). This may suggest that the intervention effect has absorbed some differences between treated practices due to an underlying practice-specific time trend (which can happen when policies are implemented at different points in time in different units, ie, the practice time trend which was occurring already can drive the results, so once we control for this, the estimated effect is driven towards zero). 18 The ES, however, remained similar to the result reported above.

We were unable to predict wave 1 entry from the characteristics we included in our logistic regression model. Thus, we conclude that selection bias into early adoption, based on these characteristics at least, was minimal. However, this does not preclude the presence of selection bias based on unmeasured characteristics.

When we removed wave 1 practices (assuming these to be at most risk of selection bias, if it did indeed occur), statistical power was reduced (as expected), and the SEs of our estimates were inflated. Subsequently, we found no significant results following this robustness check. The estimate for inpatient non-elective admissions nevertheless remained negative (ie, in favour of the intervention—see online supplementary material appendices for full list of estimates following this robustness check).

For direct effects of the intervention, this study finds some statistically significant differences between groups, although effects are very small. The results of our DDD analysis show that even the highest risk patients (as defined by the risk prediction tool) treated did not benefit from the intervention, and in fact admissions for a number of outcomes (inpatient non-electives, A&E visits and inpatient length of stay) increased slightly for these patients.

Additional analysis at the practice level finds indications of potentially small positive spillover effects of integrated working at a higher system level. In particular, we identified a possible reduction in inpatient non-elective admissions (which, however, did not hold up to our robustness check). However, even if these effects are caused by the intervention, which this study cannot prove beyond doubt, the absolute difference observed in the analysis is small. 26 For an average practice of approximately 6000 patients, this would equate to an estimated difference (not an absolute reduction) of −45.6 (95% CI −84.0 to −6.6) inpatient non-elective admissions in a year compared to usual care. If we estimate the average cost of an inpatient non-elective admission to be £1489, 28 this would potentially translate to a £67 898 (95% CI £125 076 to £9827) difference compared to usual care, before accounting for intervention costs. While we did not have data on the precise intervention costs of PICT, the national Directed Enhanced Service (DES), which incentivises similar case management interventions, paid an average-sized practice £5175 for implementing the intervention in 2013/2014. 29 This extra incentive cost of course does not account for actual additional costs of running the intervention, for example, physician time, overheads and opportunity cost of a fairly time-intensive intervention, which would also need to be considered. Additionally, our analysis found no significant effect on total secondary care costs realised during the study period, with a presumable increase in primary care costs to run the intervention (although we did not have data available on primary care costs, so cannot say for certain). Therefore, beyond the cautions we have identified for this potential spillover benefit (ie, absence of a primary effect, and not holding up to robustness checks), cost-effectiveness of the intervention remains questionable.

Comparison of direct and spillover effects

The apparently contradictory findings at the two levels analysed merit specific discussion. First, it is worth highlighting the small proportion of patients managed by the PICT teams directly (a stipulated 2% of each practice's highest risk adult patients). The final pool of intervention patients we analysed (n=2049), therefore, only constitutes 1.04% of the patient population in the 30 practices. The likelihood of the direct effects of the intervention being a driver for practice-level results in terms of numbers treated is therefore negligible.

Second, the patients that were targeted directly by the intervention are by definition the highest risk, and potentially beyond the means of a medical intervention causing significant impact at all. This may be particularly true in the short term, for exacerbation of what are (frequently many) LTCs. 30 Our DDD analysis adds evidence to this effect. Perhaps then, the lower risk patients in the practice would be more likely to benefit from multidisciplinary working.

Additionally, some qualitative work commissioned by the CCG separately reveals that some features of the intervention at the patient level did not occur exactly as planned. For instance, there have been problems with the implementation of the shared summary record through Graphnet, meaning the MDT case management may not have been delivered exactly as planned in every detail (beyond the practice changes introduced by the MDTs in general, and of course the case management those high-risk patients received). 31 So, if the main driver of results was the MDT working, we may plausibly expect these effects to differ by risk group (ie, the general practice being on average at lower risk).

Finally, direct and spillover effects may plausibly act through distinct mechanisms. There are some indications of wider system effects of integrated care in the literature. For example, good team ‘climate’ (ie, professional integration) 14 has been linked to superior clinical care for a number of LTCs, 32 although evidence of causation is currently lacking. 33 This is one potential mechanism that the MDT spillover effects could act through. Spillover effects, therefore, may not be dependent on the numbers captured by MDTs directly, because they go via the GP and wider care team. If practices ‘do’ MDT for a few patients, it may influence their care for everyone.

Strengths and weaknesses of the study

Our method of analysis, DD, is a robust method under certain conditions that we tested. 11 We only saw potential bias indicated by non-parallel preintervention trends for a single outcome measure at the individual level (outpatient visits), and we employ robustness checks beyond the primary analysis models. The method allows testing of a complex intervention in routine practice, with potential for greater external validity and generalisability of the findings. 12

Our results at both levels are plausible. At the individual level, we observed very little differences between the groups, as we would expect from previous literature around this intervention type. 6 At the practice level, the effect we observed was on an outcome (inpatient non-elective admissions) the intervention aimed to affect. 16

However, our study does suffer from a number of weaknesses. Unfortunately, due to the implementation of the intervention, we were not able to access individual-level data until before the point where nearly all practices implemented the intervention. This is due to an initial problem at the CCG of consenting data use for those individual patients initially included early in the intervention. This limits our ability to ascertain whether the initially recruited patients at each practice were significantly different, or benefited more or less than those recruited later to the intervention. It also prevents direct comparison of the results we saw at the practice level with those at the individual level over exactly the same period of time and limits our ability to look at any longer term effects of the intervention at the individual level. Furthermore, if spillover effects did indeed affect other patients in the practice, then the individual-level effects may be driven towards the null. This is similarly true for the DDD analysis conducted. However, these spillover effects were not strongly indicated at the practice level.

With the intervention so widespread (particularly important for an intervention incentivised nationally), we were extremely careful to choose our comparators (a crucially important step in DD analysis). We chose practices (within the same CCG) for which we knew for definite their intervention status at any time point for the practice-level analysis. Nonetheless, practices volunteered for the intervention, which can potentially introduce some selection bias at the practice level. However, we estimate this possible selection effect to be minimal based on observable practice characteristics. A common limitation of non-experimental studies, however, is we cannot discount differences based on unobservables. Adding practice fixed effects controls for any differences between practices that persist over time, as well as any hospital-level changes during the period that affect all practices.

At the individual level, we matched patients using propensity scores within the CCG achieving the necessary parallel pretrends. However, the intervention patients are selected for their immediate risk, while the control patients were selected based on their matched risk at an earlier date, which may have subsequently subsided (and hence be the reason they were indeed not recruited to the intervention). With ‘risk’, and so recruitment, defined on time-variant indicators, and so transient over time, there is potential for some bias in favour of the control group for the individual-level results in this analysis. However, with patients well matched at the initial start date, we expect to have minimised this bias.

An important weakness, constrained by the data available to us, is we were not able to analyse outcomes beyond secondary care utilisation and total cost of secondary care. While these utilisation outcomes reflect well the explicit aims of the intervention, they do not allow for a broad representation of the intervention in terms of other important potential outcomes—for example, patient health, quality of life and satisfaction with care. These additional measures could be considered when making commissioning decisions, although they were not the primary stated aim.

Results in relation to other studies

Our recent systematic review and meta-analysis looking at similar interventions likewise showed little effect across relevant health system outcomes for those involved in the intervention directly (ie, non-significant estimated pooled ES of 0.04 for secondary care use in the short term, and −0.02 in the long term). 6 However, the review did show a clear benefit in terms of patient satisfaction for these patients (statistically significant estimated pooled ES of 0.26 in the short term, and 0.35 in the long term). We were unable to replicate this finding in this study, perhaps due to the data available to us that only allowed us to look at this domain at the practice level, which is likely to be less sensitive. We hypothesised from the results of our review's subgroup analyses that case management by an MDT and involving a social worker may be more effective than other examples also included in the review (eg, single nurse case manager). Results of this subsequent study do not support this previous hypothesis. However, we also suggested that ‘low-strength’ primary care systems 17 may benefit more from the intervention (where case management may substitute for a strong primary care system). This may explain this deviation from the results of our review, which drew on evidence predominantly from a ‘low-strength’ primary care country (USA).

Looking at spillover effects from MDT case management was a strength of this paper. 14 Only a few other studies have looked at spillover effects, most notably, evaluation of the Evercare intervention. 34 However, Evercare used only a single case manager, where we might not expect to find large effects, and the study identified no spillover. 34 Analysis of MDT case management in the English ‘Integrated Care Pilots’ (ICP) likewise looked at direct and spillover effects. Roland et al identified an increase in emergency admissions and a decrease in elective admissions and outpatient attendances at the individual level. At the practice level, they identified a slight reduction in outpatient attendances. It is, however, difficult to compare these results directly with this study, with the ICP analysis evaluating six separate sites in combination, each offering slight alterations of MDT case management to different populations. Nevertheless, key differences that stand out include the presence of a social worker in the case management team in this intervention (only two smaller sites in the ICP identified input from a social worker); physical MDT meetings in this intervention rather than ‘virtual ward’ rounds (as in the ICP sites); and the GP as clinical lead in this intervention, rather than the primarily nurse-led interventions in ICP sites. 35

Implications for clinicians and policymakers

This study provides further evidence of the limited effectiveness of MDT case management aimed at generally ‘at-risk’ patients as a tool to reduce care utilisation. MDT case management targeted at high-risk patients importantly does not achieve its primary aim: reducing emergency admissions for those high-risk patients directly managed. Therefore, there may be better alternatives to this intervention, which may be other forms of case management targeted at specific conditions, which have some evidence of beneficial results—for example targeting mental health. 36 Aiming at a very small number of high-risk patients may never alleviate health system pressures alone, 30 and even the potential spillover effects of increased professional integration that may result may not be of sufficient magnitude to achieve the desired effects.

Going beyond the case management model to a more population-based approach may therefore be another avenue to explore, for example, colocation of services, or integrated electronic health records for all patients rather than just a high-risk cohort—interventions further removed from the service delivery level, but which may be regarded as a key foundation for multidisciplinary professional communication and working. We have shown here that this greater professional integration may have scope for improving measurable health system outcomes.

Future research

More work is needed to confirm these initial findings of potentially beneficial spillover effects, particularly qualitative work and process evaluation identifying plausible mechanisms. These did not stand up to our robustness checks in this analysis; however, the indication was always in the direction of favouring the intervention practices with regard to decreasing non-elective admissions at the practice level. Where it is possible, future studies looking at models of integrated care should consider spillover effects.

If commissioning bodies consider evaluation using similar robust, but cost-effective methods in the future, they should be planned from the beginning, where potential bias (discussed above) could be easily avoided. For example, a randomised stepped-wedge design may be an appropriate alternative. 37

While we improved on previous literature by including a measure of multimorbidity in our study, we only included the most basic of these, a simple count of diseases. 38 Our future research will explore outcomes stratified by different ‘types’ of multimorbidities, to observe if the intervention can be better targeted for the patients it directly affects, providing a more effective and efficient method of exploiting the potential for wider system effects.

Conclusions

We show that MDT case management does not fulfil its primary aim, preventing emergency admissions for the high-risk patients it targets. This accords with our previous findings. We show here that the highest risk patients (as identified by the risk tool) receiving the intervention in fact slightly increased admissions in many domains targeted for decrease by the intervention. We do, however, show some indications of beneficial spillover effects of MDT working at the practice level worthy of further exploration. The results highlight the importance of ongoing work on effective ways of avoiding admissions. 36

Acknowledgments

The authors wish to thank Central Manchester CCG for the data they provided and the time they took to explain to us the details of the intervention.

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Twitter Follow Jonathan Stokes at @DukeStokes and Peter Bower at @Bowercpcman

Contributors JS has had the main responsibility for calculating statistics and writing the paper. JS, SRK, KC and PB designed the analysis plan, and drafted and revised the paper. JS and SRK conducted the analysis.

Funding This work was funded by the National Institute for Health Research Greater Manchester Primary Care Patient Safety Translational Research Centre (NIHR GM PSTRC). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Data sharing statement No additional data are available.

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1 Definitions

Understanding the terminology used to describe studying in more than one subject and the differences between them is important, as you will often come across these terms used interchangeably. For example, the word ‘discipline’ itself used to be related to the specific rules and processes that had to be followed in order to become an expert in a particular subject. Now, however, the terms ‘subject’ and ‘discipline’ are used interchangeably, as you will learn throughout this course.

Firstly, let’s explore meanings of, and differences between, the terms ‘multidisciplinarity’ and ‘interdisciplinarity’.

Multidisciplinarity is where two or more academic disciplines collaborate for a specific purpose, for instance, when computer scientists, psychologists and sociologists cooperate in the design of human/computer interfaces. Although a multidisciplinary approach uses the skills and knowledge from more than one academic discipline, the use of knowledge from different disciplines remains distinct , even though the differences between the disciplines can be quite subtle. For example, architects, engineers and quantity surveyors commonly work together on construction projects, each applying their specialist knowledge to their own area of expertise. When a project is completed, each of the specialists return to their own area of expertise to start other projects.

A multidisciplinary approach is also often used in healthcare and social work, where patients’ clinical and healthcare needs are met by a multidisciplinary team; for example, nurses, social workers, general practitioners and psychotherapists may work together in multidisciplinary teams to address such problems as the rehabilitation of stroke patients (SIGN, 2002).

This illustration shows a number of figures represented. At the centre is the patient, and around the patient are physiotherapists, social workers, psychotherapists, nurses and general practitioners.

In the context of The Open University, our ‘Open’ qualifications are considered to be multidisciplinary , as you study individual courses independently of each other. There is no formal requirement for students to bring together the knowledge and skills gained from each course, but they can all contribute to their overall qualification).

Interdisciplinarity differs from multidisciplinarity because the different disciplines work together to produce new knowledge and understanding. This can yield new understandings that would not have been possible if different experts had worked only in their own discipline area. For example, sociologists may work with psychologists and economists to examine issues affecting women returning to work after having children and the impact of this on society. Researchers from different disciplines therefore bring their own methods and insights to a particular project, or to solve a particular problem.

Studying in this way offers a unique opportunity to understand how this knowledge could be brought together in an interdisciplinary way and applied in different contexts, and the importance of this to real-life scenarios. It is therefore important for you to be able to make these connections, even if you are not technically studying in an interdisciplinary way.

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• Multidisciplinary care

Evidence review I

NICE Guideline, No. 206

National Guideline Centre (UK) .

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1. Multidisciplinary care

1.1. review question.

• In people with ME/CFS, what is the clinical and cost-effectiveness of different models of multidisciplinary care?

1.1.1. Introduction

People with ME/CFS can require care from a variety of different health and social care professionals because of the problems associated with ME/CFS and its association with a number of co-morbidities. Care may be required from professionals from primary, community, secondary and tertiary care at different stages and severities of the illness. This can include delivery of particular interventions and programmes over shorter timeframes, as well as ongoing monitoring and review. NICE has developed general guidance on principles of organisation of care. The NICE guideline on Patient experience makes recommendations on continuity of care and co-ordination of services based on patient needs and priorities. The NICE guideline on Multimorbidity recognises the potential burden of interactions with multiple services.

1.1.2. Summary of the protocol

For full details see the review protocol in Appendix A .

PICO characteristics of review question.

1.1.3. Methods and process

This evidence review was developed using the methods and process described in Developing NICE guidelines: the manual . Methods specific to this review question are described in the review protocol in appendix A and the methods document.

Declarations of interest were recorded according to NICE’s conflicts of interest policy .

1.1.4. Effectiveness evidence

1.1.4.1. included studies.

A search was conducted for randomised trials comparing the effectiveness of treatment strategies delivered by different multidisciplinary teams versus each other or a suitable comparator (i.e. no MDT care) for people with diagnosed ME/CFS.

Very little evidence was identified and the committee discussed if the two studies identified did answer the review question comparing different MDTs. They agreed to include the studies on the basis this was the only evidence and acknowledging that while the studies did not compare different MDTs they did compare different approaches to delivering care for people with ME/CFS.

Two RCTs were included in the review; 13 , 22 – 24 these are summarised in Table 2 below. Evidence from these studies is summarised in the clinical evidence summary below ( Table 3 ).

Both studies were adult populations and the severity of ME/CFS was mixed or unclear. MDT care was compared with primary care, and with care from a psychologist/behavioural therapist.

See also the study selection flow chart in Appendix C , study evidence tables in Appendix D , forest plots in Appendix E and GRADE tables in Appendix F .

1.1.4.2. Excluded studies

See the excluded studies list in Appendix J .

1.1.5. Summary of studies included in the effectiveness evidence

Summary of studies included in the evidence review.

See Appendix D for full evidence tables

1.1.6. Summary of the effectiveness evidence

Clinical evidence summary: Clinical psychologist + physiotherapist + occupational therapist (attention control) versus primary care; adults, severity mixed or unclear.

Clinical evidence summary: Physical therapist + occupational therapist + psychologist + social worker versus psychologist/behavioural therapist; adults, severity mixed or unclear.

See Appendix F for full GRADE tables.

More information on the minimally important differences (MIDs) used and the interpretation can be found in Appendix K of this review and the Methods Chapter of this guideline.

1.1.7. Economic evidence

1.1.7.1. included studies.

Two health economic studies with a relevant comparison were included in this review. 13 , 22 These are summarised in the health economic evidence profile below ( Table 5 ) and the health economic evidence tables in Appendix H . Both studies are included in the review of clinical studies (above) and in the review of non-pharmacological interventions (Evidence Review G).

1.1.7.2. Excluded studies

No relevant health economic studies were excluded due to assessment of limited applicability or methodological limitations.

See also the health economic study selection flow chart in Appendix G .

1.1.8. Summary of included economic evidence

Health economic evidence profile: Multidisciplinary care vs usual care.

1.1.9. Economic model

Original economic modelling was not conducted.

1.1.10. Evidence statements

1.1.10.1. economic.

• One cost–utility analysis found that multidisciplinary rehabilitation (physical therapist, occupational therapist, psychologist and social worker) was not cost effective compared to cognitive behavioural therapy by a psychologist for adults with ME/CFS (ICER: £106,000 per QALY gained). This analysis was assessed as partially applicable with potentially serious limitations.
• One cost–utility analysis found that education and support by a specialist team was cost effective compared with CBT for adults with ME/CFS (ICER: £7,900 per QALY gained). This analysis was assessed as partially applicable with potentially serious limitations.

1.2. The committee’s discussion and interpretation of the evidence

The committee discussed this evidence with the findings from the reviews on access to care (report C), diagnosis (report D), management (reports F and G) and the reports on Children and Young people ( Appendix 1 ) and people with severe ME/CFS ( Appendix 2 ). Where relevant, this is noted.

1.2.1. The outcomes that matter most

Quality of life, pain, fatigue/fatigability, physical functioning, cognitive functioning, sleep quality, adverse effects, psychological outcomes, patient satisfaction, benefit status, employment and educational attendance, diagnostic status, co-morbidities, activity monitoring and post exertional malaise (PEM)/post exertional symptom exacerbation (PESE) were all agreed by the committee to be critical outcomes for decision making.

These outcomes reflect the direct impact ME/CFS symptoms have on a person (specifically levels of pain, fatigue, physical functioning cognitive functioning, sleep quality, psychological outcomes, PEM/PESE, and in turn the impact on quality of life (specifically benefit status, employment and educational attendance).

The impact of the different models of MDTs can be measured by the outcomes listed above, if a particular model is successful symptoms would be managed appropriately and the impact on a person’s life would be minimised compared to a strategy (including no review) that did not identify worsening symptoms.

The effectiveness of an MDT is also reflected in these outcomes: diagnostic status, co-morbidity identification, adverse effects and patient satisfaction. Diagnostic status and comorbidity review and identification are key to ensuring that a person is receiving the correct intervention and management for their condition or conditions. If this is not picked up by an MDT this would have a detrimental impact on the person.

Any contact with health and social care services will have an impact on physical and emotional energy levels of people with ME/CFS. It is key that any contact does not make people with ME/CFS worse and their needs are understood so that they can access the service successfully. Adverse effects and patient satisfaction address these concerns.

The committee acknowledged the lack of existing objective outcome measures of effectiveness of interventions for ME/CFS and the limitations of subjective measures (see Professor Edwards expert testimony – Appendix 3 : Expert testimonies). Only validated outcome measurement scales were included in the evidence review.

1.2.2. The quality of the evidence

No evidence was identified for children and young people. No evidence was identified for adults for the outcomes; pain, sleep quality, adverse effects, patient satisfaction, benefit status/employment/school attendance/school absences, update of diagnostic status, comorbidities, PESE/PEM, care needs, and impact on families and carers.

Evidence from 2 randomised trials with follow up over 6 months was identified for this review. The studies compared different approaches for delivering care; one compared an MDT (with a clinical psychologist, physiotherapist and an occupational therapist) to standard care managed in primary care and the other compared a MDT (with a physical therapist, occupational therapist, psychologist and social worker) to a psychologist or behavioural therapist.

The quality of the evidence ranged from low to very low. The main reasons for downgrading were due to risk of bias, indirectness and imprecision. There was a lack of blinding in the studies due to the nature of the interventions. This, combined with the mostly subjective outcomes, resulted in a high risk of performance bias.

The committee discussed the CDC 1994 diagnostic criteria used in the studies to recruit eligible participants. The committee have identified PEM as an essential symptom that is central to the diagnosis of ME/CFS (see evidence report D: diagnosis) and the CDC 1994 criteria does not include this as a compulsory requirement, the studies did not give further information on the numbers of people with PEM. The committee agreed that a population diagnosed with such criteria may not accurately represent the ME/CFS population and that people experiencing PEM are likely to respond differently to treatment than those who do not experience PEM and this raised concerns over the generalisability of findings to the ME/CFS population. It was therefore agreed to downgrade the evidence for population indirectness. The studies had small sample sizes increasing the uncertainty around the point estimate.

1.2.3. Benefits and harms

Mdt comparisons.

The committee acknowledged that the evidence comparing different MDTs was limited and insufficient to base a recommendation for any one type of MDT or a core MDT composition. They noted the only outcomes reported were quality of life, fatigue, cognitive function, psychological and exercise measures. In the study comparing multidisciplinary rehabilitation to CBT delivered by a psychologist/behavioural therapist, fatigue was lower showing clinical benefit in the group receiving multidisciplinary rehabilitation, but the committee noted this was very low quality evidence and were not confident about the effect. No clinically important difference was observed for any other of the outcomes.

The committee noted the evidence came from small studies with indirect populations; both studies recruited participants using the 1994 CDC criteria and one was based in the Netherlands and this limited the relevance of the results to people with ME/CFS and current NHS practice. The committee noted the studies only included adults and did not reflect MDTs caring for children and young people.

Expert testimony

Dr Husain gave an overview of the Persistent Physical Symptoms Research and Treatment Unit at South London and Maudsley (SLAM) NHS Foundation Trust and the units approach towards the care of people with ME/CFS. Dr Husain noted the service also sees patients with fatigue from other causes such as post-chemotherapy fatigue, MS, fibromyalgia. The criteria for entry to specialist services varies across the country, and some only see people who meet specific diagnostic criteria. The SLAM MDT is composed of psychiatrists, psychologists and a physiotherapist and there is a holistic approach to assessment and management. The service receives referrals from across England with most from Greater London. The initial appointment is a 2-hour assessment, people receive up to 20 sessions with further follow up sessions if required. If other medical conditions are suspected (either as a differential or concomitant diagnosis), investigations are performed and the service has close links with other specialities such as rheumatology, neurology, gastroenterology. Dr Husain commented that it is important when assessing people with ME/CFS that differential and co-existing conditions are considered. It is important to ensure that other causes of fatigue are considered and to assess for mood disorders, such as depression which are common in long term conditions. Dr Husain noted that often people have seen several specialists before they are referred to their service. The care and support plan is developed with the person with ME/CFS and involves families and carers identifying what the person wants to do and to determine limitations. The focus of management is on modifiable current factors that can impact on symptoms and overall wellbeing and not on a cure. The primary management options the service is funded to provide are CBT or GET (as in the NICE guideline ME/CFS published in 2007) and this is reflected in in the composition of the MDT. If input from other HCPs is required such as a dietitian or occupational therapist referral to other services is required. The service manages people with a wide severity of symptoms and disability and has some provision for the home-based management of the people with severe or very severe ME/CFS. Home based management is limited by geographical location, number of staff available, time, and funding. Dr Husain noted that overall non-attendance rates have gone down since virtual consultations have been introduced as a result of COVID; this may reflect the difficulty some people with ME/CFS have in attending appointments in person. Dr Husain noted that with good engagement, assessment, collaboration, taking the patients seriously and making firm diagnoses of conditions such as ME/CFS when appropriate, addresses issues such as stigma. He noted that in his unit, this the hallmark of the service and patients are almost always happy to proceed and the unit has several years of very positive patient feedback all of which is collected anonymously. (see appendix 3 : Expert Testimonies for Dr Husain’s written testimony).

After Dr Husain had left the meeting the committee discussed the expert testimony presented by Dr Husain and agreed that there are MDT approaches in specialist ME/CFS services but there is variation in how they are run across the NHS. The committee noted services are led by a variety of specialities, including psychiatry, psychology, infectious diseases, immunology, neurology, physiotherapy and occupational therapy. The committee commented that this has led to misunderstanding when people with ME/CFS have been referred to some services feeling there is a mismatch between their illness experience and the speciality. The committee noted this was not a specific comment about SLAM. The committee acknowledged this variety of specialities is largely historical and a result of clinical interests and previous funding allocation.

The committee recognised that although the services for ME/CFS are situated within different specialities they have access to physicians, physiotherapy and psychologists and some have access to occupational therapy and nursing input.

While the committee were unable to draw conclusions about the specific composition of a multidisciplinary team based on the evidence they agreed that good care for people with ME/CFS results from access to an integrated team of health and social care professionals that are trained and experienced in the management of ME/CFS.

The committee agreed it was important to make consensus recommendations based on their experience about the health and social care support and expertise needed by people with ME/CFS. The committee recommended that care for people with ME/CFS should be provided using a co-ordinated multidisciplinary approach that includes health and social care professionals with expertise in relevant areas. The committee considered that it was important to outline the expertise and skills that people with ME/CFS may need rather than identify a core team of professionals. They agreed that expertise in medical assessment and diagnosis, developing a personalised care and support plan, self-management strategies (including energy management), symptom management including prescribing and medicines management, managing flare ups and relapse, activities of daily living (such as personal care including dental health, housework, food preparation and eating), physical, psychological and emotional and social well-being, diet and nutrition, mobility (including access to aids and rehabilitation services), social care support and support with engagement at work, education and social activities were crucial for the care of people with ME/CFS.

The committee noted that ME/CFS affects each person differently and varies widely in severity. The fluctuating nature of ME/CFS can mean support needs can change and access to different expertise is needed at different times. This is particularly true of people with severe or very severe ME/CFS who have very complex needs that in the committee’s opinion are not always sufficiently met (see report on people with severe ME/CFS).

The committee recognised certain interventions should only be delivered or overseen by healthcare professionals who are part of a specialist team. The committee recognise there is a crossover in skills within specialist teams, occupational therapists and physiotherapists both support people with ME/CFS with activity management and support with symptoms. They noted that in specific circumstances the expertise of a specific professional role may be needed, for example a ME/CFS specialist physiotherapist to oversee physical activity programmes or to support colleagues where there are concerns around the physical effects of illness, injury or comorbidities with developing physical activity or exercise programmes

See management reports F & G where the committee outline where it is important that professionals trained in ME/CFS deliver areas of care. The committee agreed that medical assessment and diagnosis would typically require access to a ME/CFS specialist physician or a GP with a special interest in ME/CFS but noted there are highly trained ME/CFS advanced practitioners that can fulfil this role.

Co-ordination of care

They noted that a multidisciplinary approach is required for all long term and complex conditions and this requires good communication and coordination across different services. The committee highlighted the importance of shared care between primary care and specialist teams. In the evidence reports on access to care (evidence report C) and in the commissioned reports on children and young people ( appendix 1 ), and people with severe ME/CFS ( appendix 2 ) the limited time that GPs have to offer in a consultation is highlighted. Some of the committee members working in specialist teams noted they had 1- 2-hour initial appointments with people with suspected ME/CFS and access to professionals who had the time to develop a personalised care and support plan. The committee acknowledged that GPs did not have enough time to carry out the assessments needed to confirm a diagnosis of ME/CFS or to develop a care and support plan in a single standard appointment. The committee recommended that once someone with suspected ME/CFS has had persistent symptoms indicating ME/CFS for 3 months the person should be referred to a specialist team for confirmation of the diagnosis.

Access to ME/CFS specialist teams

ME/CFS specialist teams provide the expertise and skills that are required to provide appropriate care to people with ME/CFS and the committee discussed the availability of specialist care in the context of recommending MDTs and for referral for the confirmation of diagnosis and development of a care and support plan. Specialist services commonly accept referrals from across England and Wales and is almost always a research centre and shared with the academic side of the NHS Trust they are based in.

Drawing on their experience of the ME/CFS specialist services the committee described the different compositions of ME/CFS specialist teams. A ME/CFS specialist team can have a range of healthcare professionals with expertise in assessing, diagnosing, treating and managing ME/CFS. ME/CFS specialist teams commonly comprise of medically trained clinicians (who have specialist training, specialisms include rheumatology, rehabilitation medicine, endocrinology, infectious disease, neurology, immunology, general practice, paediatrics) and access to health professionals that specialise in ME/CFS, these may include physiotherapists, exercise physiologists, occupational therapists, dieticians, clinical and/or counselling psychologists. The committee agreed it was important that a ME/CFS specialist team has access to a medical clinician to understand when further investigations should be done and the symptoms that may indicate a differential or coexisting condition. The committee noted that many people referred to a ME/CFS specialist service do not end up with a ME/CFS diagnosis. The committee noted that initial appointments to a ME/CFS specialist team could be scheduled for 1-2 hours. The committee were aware that up to a third of ME/CFS services did not have medical input and there are paediatric ME/CFS services that report having no specialist paediatrician dedicated to their service and often rely on a general paediatrician to confirm or refute diagnosis which results in wide variation in pathways and treatment. Children and young people are likely to be cared for under local or regional paediatric teams that have experience working with children and young people with ME/CFS in collaboration with ME/CFS specialist centres.

The committee discussed the importance of specialist teams either employing or having access to allied health professionals that have expertise in managing ME/CFS to support people developing and then supporting personalised care and support plans (for example, physiotherapists, occupational therapists, dieticians, clinical psychologists).

The committee acknowledged that specialist teams are limited in number and in some areas of England and Wales are non-existent. As a result, referral to specialist teams can be difficult; committee members were aware of referrals taking many months and in some cases years.

The committee were aware of different referral processes across England and Wales, with some areas using a tick box criteria that is assessed by an administrator. The committee agreed that referral should be based on the criteria outlined in this guideline but acknowledged that a rigid tick-box criteria can be unhelpful and does not allow for the complexities in symptom assessment that can be present in people with ME/CFS. This approach can result in missed opportunities for early diagnosis and management and referrals should go directly to a specialist team for assessment. Early diagnosis by a specialist team allows early management and follow up that may prevent deterioration in symptoms and wellbeing.

In the committee’s experience a shared care approach works well, providing the person with ME/CFS and their GP access to expert advice and education when necessary. Committee members noted that although funding was usually limited to a treatment course people with ME/CFS and their GPs should always have access to specialist information and resources. One example of this was a triage telephone service where people with ME/CFS could contact their specialist team for advice about symptoms or a relapse and facilitate an examination and further investigations if indicated. Committee members working with children and young people noted this continuing contact was particularly important in supporting non specialists caring for people with ME/CFS.

The committee noted that good co-ordination of care and communication across services was particularly important when young people move to adult services and cross referenced to the NICE guideline on transition from children’s to adults’ services for young people using health or social care services . Some committee members were aware of specific examples of advice in specialist teams for young people with ME/CFS moving to adult services.

As part of the recommendations on specialist care the committee discussed the importance of a named contact in the ME/CFS specialist team. There are the recognised benefits of having one point of contact that can help support someone to navigate access to health and social care and to communicate and co-ordinate care between services. However, the committee noted that access to a specialist team with many professionals can have both favourable and unfavourable consequences for someone with ME/CFS. This can result in a person having contact and appointments with several different people and this can impact negatively on the person’s health potentially worsening symptoms. To avoid this unintended consequence of a multidisciplinary care it is important there is one point of contact to co-ordinate care. This was common practice in the committee’s experience, and they noted that although during specific treatments one professional is predominantly involved, other team members are easily accessible and can be more involved if the need arises.

One of the themes identified throughout the guideline reviews is a lack of belief from health and social care professionals that ME/CFS exists. The committee were aware of the importance of the therapeutic alliance and the shared beliefs about the cause of ME/CFS. The committee noted this was particularly important for children and young people and they should be involved in the decision making about their key worker.

1.2.4. Cost effectiveness and resource use

Both clinical trials included in the review had conducted an economic analysis. They were each deemed to be partially applicable, for example, they could have included some patients who did not have post exertional malaise. They both had potentially serious limitations: they were all at potentially high risk of bias due to lack of blinding.

In the first study multidisciplinary rehabilitation yielded an improvement in fatigue and slightly more QALYs than CBT but at £106,000 per QALY gained, the cost was too high for multidisciplinary rehabilitation to be considered cost effective.

In the second study, an education and support programme provided by a specialist team had higher cost and better quality of life than GP-led usual care. The study sample size was small, and the baseline differences were quite large and drug costs were approximated from limited data, so it was difficult to draw any conclusions about cost effectiveness. However, the trend indicated that education and support would be cost effective at £13,300 per QALY gained.

Overall, the quantitative evidence was limited and the cost effectiveness of an ME/CFS specialist multidisciplinary teams is therefore uncertain. Cost effectiveness of a team is likely to depend on the staff-mix in the team and the therapies offered.

• Many people with ME/CFS have experienced long delays to diagnosis and poor sometimes resulting in worsening of symptoms or even disease progression. Sometimes staff have not believed that the disease or symptoms are real.
• The presence of a specialist team was a facilitator of faster diagnosis and better care for people with ME/CFS.
• Patients and professionals identified the need for a clear clinical management. pathway for ME/CFS and a specialist team would make that pathway more explicit.
• There is a need for a source of information and support for non-specialist health care professionals.

There is evidence that people with ME/CFS have very poor quality of life, worse than most other chronic conditions, 7 and that they require higher levels of health care resource than the general population 4 . So, there is potential for a service that can improve the course of this disease to have a benefit in terms of both health outcome and resource use. The committee recommended that specialist multidisciplinary teams (including a named contact) be used to confirm diagnosis, establish a treatment plan and provide support for primary care services. The exact cost effectiveness of a specialist team is uncertain, but the committee were convinced that their provision would be a good use of NHS resources, leading to faster access to appropriate care and substantially better patient outcomes for people with ME/CFS.

• self-management strategies, including energy management
• symptom management
• managing flares and relapse
• activities of daily living
• emotional wellbeing, including family and sexual relationships
• diet and nutrition
• mobility and avoiding falls and problems from loss of dexterity, including access to aids and rehabilitation services
• social care and support
• support to engage in work, education, social activities and hobbies.

Most people will only require a few elements and only at specific points in time, with emphasis on early assessment and developing a personalised care and support plan. It is intended that appropriate advice and care early will reduce health and care costs downstream by reducing the risk of progression to more severe disease.

1.2.5. Other factors the committee took into account

The committee discussed the need to improve communication between specialist teams. It is not unusual for people with a suspected diagnosis of ME/CFS to be investigated for other conditions and this is an important role of the ME/CFS specialist team. These referrals to other specialities are not necessarily concurrent. Direct consultant to consultant referrals could help provide context for the referrals and avoid further delays with the understanding that people are referred back to ME/CFS specialist teams if their ME/CFS type symptoms persist once treated for any other conditions.

Appendix A. Review protocols

A.1. Review protocol for multidisciplinary care (PDF, 326K)

Appendix B. Literature search strategies

The literature searches for this review are detailed below and complied with the methodology outlined in Developing NICE guidelines: the manual. 11

For more information, please see the Methodology review published as part of the accompanying documents for this guideline.

B.1. Clinical search literature search strategy (PDF, 340K)

B.2. Health economics literature search strategy (PDF, 283K)

Appendix C. Effectiveness evidence study selection

Figure 1. Flow chart of clinical study selection for the review of multidisciplinary care (PDF, 136K)

Appendix D. Effectiveness evidence

Download PDF (230K)

Appendix E. Forest plots

E.1. Clinical psychologist + physiotherapist + occupational therapist (attention control) versus primary care; adults, severity mixed or unclear (PDF, 147K)

E.2. Physical therapist + occupational therapist + psychologist + social worker versus psychologist/behavioural therapist; adults, severity mixed or unclear (PDF, 179K)

Appendix F. GRADE tables

Table 9. Clinical evidence profile: Clinical psychologist + physiotherapist + occupational therapist (attention control) versus primary care; adults, severity mixed or unclear (PDF, 273K)

Table 10. Clinical evidence profile: Physical therapist + occupational therapist + psychologist + social worker versus psychologist/behavioural therapist; adults, severity mixed or unclear (PDF, 161K)

Appendix G. Economic evidence study selection

Download PDF (220K)

Appendix H. Economic evidence tables

Download PDF (228K)

Appendix I. Health economic model

No original economic modelling was undertaken.

Appendix J. Excluded studies

J.1. clinical studies.

Download PDF (149K)

J.2. Health Economic studies

Published health economic studies that met the inclusion criteria (relevant population, comparators, economic study design, published 2004 or later and not from non-OECD country or USA) but that were excluded following appraisal of applicability and methodological quality are listed below. See the health economic protocol for more details.

Appendix K. MIDs for continuous outcomes

K.1. Clinical psychologist + physiotherapist + occupational therapist (attention control) versus primary care; adults, severity mixed or unclear (PDF, 144K)

K.2. Physical therapist + occupational therapist + psychologist + social worker versus psychologist/behavioural therapist; adults, severity mixed or unclear (PDF, 142K)

Evidence reviews underpinning recommendations and research recommendations in the NICE guideline

These evidence reviews were developed by the National Guideline Centre

Disclaimer : The recommendations in this guideline represent the view of NICE, arrived at after careful consideration of the evidence available. When exercising their judgement, professionals are expected to take this guideline fully into account, alongside the individual needs, preferences and values of their patients or service users. The recommendations in this guideline are not mandatory and the guideline does not override the responsibility of healthcare professionals to make decisions appropriate to the circumstances of the individual patient, in consultation with the patient and/or their carer or guardian.

Local commissioners and/or providers have a responsibility to enable the guideline to be applied when individual health professionals and their patients or service users wish to use it. They should do so in the context of local and national priorities for funding and developing services, and in light of their duties to have due regard to the need to eliminate unlawful discrimination, to advance equality of opportunity and to reduce health inequalities. Nothing in this guideline should be interpreted in a way that would be inconsistent with compliance with those duties.

NICE guidelines cover health and care in England. Decisions on how they apply in other UK countries are made by ministers in the Welsh Government , Scottish Government , and Northern Ireland Executive . All NICE guidance is subject to regular review and may be updated or withdrawn.

• Cite this Page National Guideline Centre (UK). Multidisciplinary care: Myalgic encephalomyelitis (or encephalopathy) / chronic fatigue syndrome: diagnosis and management: Evidence review I. London: National Institute for Health and Care Excellence (NICE); 2021 Oct. (NICE Guideline, No. 206.)
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• NICE Guideline 206: Myalgic encephalomyelitis (or encephalopathy)/chronic fatigue syndrome: diagnosis and management

Supplemental NICE documents

• Appendix 1: Involving children and young people (PDF)
• Appendix 2: Involving adults with severe ME/CFS symptoms (PDF)
• Appendix 3: Expert testimonies (PDF)
• Methods (PDF)

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Research design: the methodology for interdisciplinary research framework

• Open access
• Published: 27 April 2017
• Volume 52 , pages 1209–1225, ( 2018 )

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• Hilde Tobi   ORCID: orcid.org/0000-0002-8804-0298 1 &
• Jarl K. Kampen 1 , 2  

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Many of today’s global scientific challenges require the joint involvement of researchers from different disciplinary backgrounds (social sciences, environmental sciences, climatology, medicine, etc.). Such interdisciplinary research teams face many challenges resulting from differences in training and scientific culture. Interdisciplinary education programs are required to train truly interdisciplinary scientists with respect to the critical factor skills and competences. For that purpose this paper presents the Methodology for Interdisciplinary Research (MIR) framework. The MIR framework was developed to help cross disciplinary borders, especially those between the natural sciences and the social sciences. The framework has been specifically constructed to facilitate the design of interdisciplinary scientific research, and can be applied in an educational program, as a reference for monitoring the phases of interdisciplinary research, and as a tool to design such research in a process approach. It is suitable for research projects of different sizes and levels of complexity, and it allows for a range of methods’ combinations (case study, mixed methods, etc.). The different phases of designing interdisciplinary research in the MIR framework are described and illustrated by real-life applications in teaching and research. We further discuss the framework’s utility in research design in landscape architecture, mixed methods research, and provide an outlook to the framework’s potential in inclusive interdisciplinary research, and last but not least, research integrity.

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1 Introduction

Current challenges, e.g., energy, water, food security, one world health and urbanization, involve the interaction between humans and their environment. A (mono)disciplinary approach, be it a psychological, economical or technical one, is too limited to capture any one of these challenges. The study of the interaction between humans and their environment requires knowledge, ideas and research methodology from different disciplines (e.g., ecology or chemistry in the natural sciences, psychology or economy in the social sciences). So collaboration between natural and social sciences is called for (Walsh et al. 1975 ).

Over the past decades, different forms of collaboration have been distinguished although the terminology used is diverse and ambiguous. For the present paper, the term interdisciplinary research is used for (Aboelela et al. 2007 , p. 341):

any study or group of studies undertaken by scholars from two or more distinct scientific disciplines. The research is based upon a conceptual model that links or integrates theoretical frameworks from those disciplines, uses study design and methodology that is not limited to any one field, and requires the use of perspectives and skills of the involved disciplines throughout multiple phases of the research process.

Scientific disciplines (e.g., ecology, chemistry, biology, psychology, sociology, economy, philosophy, linguistics, etc.) are categorized into distinct scientific cultures: the natural sciences, the social sciences and the humanities (Kagan 2009 ). Interdisciplinary research may involve different disciplines within a single scientific culture, and it can also cross cultural boundaries as in the study of humans and their environment.

A systematic review of the literature on natural-social science collaboration (Fischer et al. 2011 ) confirmed the general impression of this collaboration to be a challenge. The nearly 100 papers in their analytic set mentioned more instances of barriers than of opportunities (72 and 46, respectively). Four critical factors for success or failure in natural-social science collaboration were identified: the paradigms or epistemologies in the current (mono-disciplinary) sciences, the skills and competences of the scientists involved, the institutional context of the research, and the organization of collaborations (Fischer et al. 2011 ). The so-called “paradigm war” between neopositivist versus constructivists within the social and behavioral sciences (Onwuegbuzie and Leech 2005 ) may complicate pragmatic collaboration further.

It has been argued that interdisciplinary education programs are required to train truly interdisciplinary scientists with respect to the critical factor skills and competences (Frischknecht 2000 ) and accordingly, some interdisciplinary programs have been developed since (Baker and Little 2006 ; Spelt et al. 2009 ). The overall effect of interdisciplinary programs can be expected to be small as most programs are mono-disciplinary and based on a single paradigm (positivist-constructivist, qualitative-quantitative; see e.g., Onwuegbuzie and Leech 2005 ). We saw in our methodology teaching, consultancy and research practices working with heterogeneous groups of students and staff, that most had received mono-disciplinary training with a minority that had received multidisciplinary training, with few exceptions within the same paradigm. During our teaching and consultancy for heterogeneous groups of students and staff aimed at designing interdisciplinary research, we built the framework for methodology in interdisciplinary research (MIR). With the MIR framework, we aspire to contribute to the critical factors skills and competences (Fischer et al. 2011 ) for social and natural sciences collaboration. Note that the scale of interdisciplinary research projects we have in mind may vary from comparably modest ones (e.g., finding a link between noise reducing asphalt and quality of life; Vuye et al. 2016 ) to very large projects (finding a link between anthropogenic greenhouse gas emissions, climate change, and food security; IPCC 2015 ).

In the following section of this paper we describe the MIR framework and elaborate on its components. The third section gives two examples of the application of the MIR framework. The paper concludes with a discussion of the MIR framework in the broader contexts of mixed methods research, inclusive research, and other promising strains of research.

2 The methodology in interdisciplinary research framework

2.1 research as a process in the methodology in interdisciplinary research framework.

The Methodology for Interdisciplinary Research (MIR) framework was built on the process approach (Kumar 1999 ), because in the process approach, the research question or hypothesis is leading for all decisions in the various stages of research. That means that it helps the MIR framework to put the common goal of the researchers at the center, instead of the diversity of their respective backgrounds. The MIR framework also introduces an agenda: the research team needs to carefully think through different parts of the design of their study before starting its execution (Fig.  1 ). First, the team discusses the conceptual design of their study which contains the ‘why’ and ‘what’ of the research. Second, the team discusses the technical design of the study which contains the ‘how’ of the research. Only after the team agrees that the complete research design is sufficiently crystalized, the execution of the work (including fieldwork) starts.

The Methodology of Interdisciplinary Research framework

Whereas the conceptual and technical designs are by definition interdisciplinary team work, the respective team members may do their (mono)disciplinary parts of fieldwork and data analysis on a modular basis (see Bruns et al. 2017 : p. 21). Finally, when all evidence is collected, an interdisciplinary synthesis of analyses follows which conclusions are input for the final report. This implies that the MIR framework allows for a range of scales of research projects, e.g., a mixed methods project and its smaller qualitative and quantitative modules, or a multi-national sustainability project and its national sociological, economic and ecological modules.

2.2 The conceptual design

Interdisciplinary research design starts with the “conceptual design” which addresses the ‘why’ and ‘what’ of a research project at a conceptual level to ascertain the common goals pivotal to interdisciplinary collaboration (Fischer et al. 2011 ). The conceptual design includes mostly activities such as thinking, exchanging interdisciplinary knowledge, reading and discussing. The product of the conceptual design is called the “conceptual frame work” which comprises of the research objective (what is to be achieved by the research), the theory or theories that are central in the research project, the research questions (what knowledge is to be produced), and the (partial) operationalization of constructs and concepts that will be measured or recorded during execution. While the members of the interdisciplinary team and the commissioner of the research must reach a consensus about the research objective, the ‘why’, the focus in research design must be the production of the knowledge required to achieve that objective the ‘what’.

With respect to the ‘why’ of a research project, an interdisciplinary team typically starts with a general aim as requested by the commissioner or funding agency, and a set of theories to formulate a research objective. This role of theory is not always obvious to students from the natural sciences, who tend to think in terms of ‘models’ with directly observable variables. On the other hand, students from the social sciences tend to think in theories with little attention to observable variables. In the MIR framework, models as simplified descriptions or explanations of what is studied in the natural sciences play the same role in informing research design, raising research questions, and informing how a concept is understood, as do theories in social science.

Research questions concern concepts, i.e. general notions or ideas based on theory or common sense that are multifaceted and not directly visible or measurable. For example, neither food security (with its many different facets) nor a person’s attitude towards food storage may be directly observed. The operationalization of concepts, the transformation of concepts into observable indicators, in interdisciplinary research requires multiple steps, each informed by theory. For instance, in line with particular theoretical frameworks, sustainability and food security may be seen as the composite of a social, an economic and an ecological dimension (e.g., Godfray et al. 2010 ).

As the concept of interest is multi-disciplinary and multi-dimensional, the interdisciplinary team will need to read, discuss and decide on how these dimensions and their indicators are weighted to measure the composite interdisciplinary concept to get the required interdisciplinary measurements. The resulting measure or measures for the interdisciplinary concept may be of the nominal, ordinal, interval and ratio level, or a combination thereof. This operationalization procedure is known as the port-folio approach to widely defined measurements (Tobi 2014 ). Only after the research team has finalized the operationalization of the concepts under study, the research questions and hypotheses can be made operational. For example, a module with descriptive research questions may now be turned into an operational one like, what are the means and variances of X1, X2, and X3 in a given population? A causal research question may take on the form, is X (a composite of X1, X2 and X3) a plausible cause for the presence or absence of Y? A typical qualitative module could study, how do people talk about X1, X2 and X3 in their everyday lives?

2.3 The technical design

Members of an interdisciplinary team usually have had different training with respect to research methods, which makes discussing and deciding on the technical design more challenging but also potentially more creative than in a mono-disciplinary team. The technical design addresses the issues ‘how, where and when will research units be studied’ (study design), ‘how will measurement proceed’ (instrument selection or design), ‘how and how many research units will be recruited’ (sampling plan), and ‘how will collected data be analyzed and synthesized’ (analysis plan). The MIR framework provides the team a set of topics and their relationships to one another and to generally accepted quality criteria (see Fig.  1 ), which helps in designing this part of the project.

Interdisciplinary teams need be pragmatic as the research questions agreed on are leading in decisions on the data collection set-up (e.g., a cross-sectional study of inhabitants of a region, a laboratory experiment, a cohort study, a case control study, etc.), the so-called “study design” (e.g., Kumar 2014 ; De Vaus 2001 ; Adler and Clark 2011 ; Tobi and van den Brink 2017 ) instead of traditional ‘pet’ approaches. Typical study designs for descriptive research questions and research questions on associations are the cross-sectional study design. Longitudinal study designs are required to investigate development over time and cause-effect relationships ideally are studied in experiments (e.g., Kumar 2014 ; Shipley 2016 ). Phenomenological questions concern a phenomenon about which little is known and which has to be studied in the environment where it takes place, which calls for a case study design (e.g., Adler and Clark 2011 : p. 178). For each module, the study design is to be further explicated by the number of data collection waves, the level of control by the researcher and its reference period (e.g., Kumar 2014 ) to ensure the teams common understanding.

Then, decisions about the way data is to be collected, e.g., by means of certified instruments, observation, interviews, questionnaires, queries on existing data bases, or a combination of these are to be made. It is especially important to discuss the role of the observer (researcher) as this is often a source of misunderstanding in interdisciplinary teams. In the sciences, the observer is usually considered a neutral outsider when reading a standardized measurement instrument (e.g., a pyranometer to measure incoming solar radiation). In contrast, in the social sciences, the observer may be (part of) the measurement instrument, for example in participant observation or when doing in-depth interviews. After all, in participant observation the researcher observes from a member’s perspective and influences what is observed owing to the researcher’s participation (Flick 2006 : p. 220). Similarly in interviews, by which we mean “a conversation that has a structure and a purpose determined by the one party—the interviewer” (Kvale 2007 : p. 7), the interviewer and the interviewee are part of the measurement instrument (Kvale and Brinkmann 2009 : p. 2). In on-line and mail questionnaires the interviewer is eliminated as part of the instrument by standardizing the questions and answer options. Queries on existing data bases refer to the use of secondary data or secondary analysis. Different disciplines tend to use different bibliographic data bases (e.g., CAB Abstracts, ABI/INFORM or ERIC) and different data repositories (e.g., the European Social Survey at europeansocialsurvey.org or the International Council for Science data repository hosted by www.pangaea.de ).

Depending on whether or not the available, existing, measurement instruments tally with the interdisciplinary operationalisations from the conceptual design, the research team may or may not need to design instruments. Note that in some cases the social scientists’ instinct may be to rely on a questionnaire whereas the collaboration with another discipline may result in more objective possibilities (e.g., compare asking people about what they do with surplus medication, versus measuring chemical components from their input into the sewer system). Instrument design may take on different forms, such as the design of a device (e.g., pyranometer), a questionnaire (Dillman 2007 ) or a part thereof (e.g., a scale see DeVellis 2012 ; Danner et al. 2016 ), an interview guide with topics or questions for the interviewees, or a data extraction form in the context of secondary analysis and literature review (e.g., the Cochrane Collaboration aiming at health and medical sciences or the Campbell Collaboration aiming at evidence based policies).

Researchers from different disciplines are inclined to think of different research objects (e.g., animals, humans or plots), which is where the (specific) research questions come in as these identify the (possibly different) research objects unambiguously. In general, research questions that aim at making an inventory, whether it is an inventory of biodiversity or of lodging, call for a random sampling design. Both in the biodiversity and lodging example, one may opt for random sampling of geographic areas by means of a list of coordinates. Studies that aim to explain a particular phenomenon in a particular context would call for a purposive sampling design (non-random selection). Because studies of biodiversity and housing obey the same laws in terms of appropriate sampling design for similar research questions, individual students and researchers are sensitized to commonalities of their respective (mono)disciplines. For example, a research team interested in the effects of landslides on a socio-ecological system may select for their study one village that suffered from landslides and one village that did not suffer from landslides that have other characteristics in common (e.g., kind of soil, land use, land property legislation, family structure, income distribution, et cetera).

The data analysis plan describes how data will be analysed, for each of the separate modules and for the project at large. In the context of a multi-disciplinary quantitative research project, the data analysis plan will list the intended uni-, bi- and multivariate analyses such as measures for distributions (e.g., means and variances), measures for association (e.g., Pearson Chi square or Kendall Tau) and data reduction and modelling techniques (e.g., factor analysis and multiple linear regression or structural equation modelling) for each of the research modules using the data collected. When applicable, it will describe interim analyses and follow-up rules. In addition to the plans at modular level, the data analysis plan must describe how the input from the separate modules, i.e. different analyses, will be synthesized to answer the overall research question. In case of mixed methods research, the particular type of mixed methods design chosen describes how, when, and to what extent the team will synthesize the results from the different modules.

Unfortunately, in our experience, when some of the research modules rely on a qualitative approach, teams tend to refrain from designing a data analysis plan before starting the field work. While absence of a data analysis plan may be regarded acceptable in fields that rely exclusively on qualitative research (e.g., ethnography), failure to communicate how data will be analysed and what potential evidence will be produced posits a deathblow to interdisciplinarity. For many researchers not familiar with qualitative research, the black box presented as “qualitative data analysis” is a big hurdle, and a transparent and systematic plan is a sine qua non for any scientific collaboration. The absence of a data analysis plan for all modules results in an absence of synthesis of perspectives and skills of the disciplines involved, and in separate (disciplinary) research papers or separate chapters in the research report without an answer to the overall research question. So, although researchers may find it hard to write the data analysis plan for qualitative data, it is pivotal in interdisciplinary research teams.

Similar to the quantitative data analysis plan, the qualitative data analysis plan presents the description of how the researcher will get acquainted with the data collected (e.g., by constructing a narrative summary per interviewee or a paired-comparison of essays). Additionally, the rules to decide on data saturation need be presented. Finally, the types of qualitative analyses are to be described in the data analysis plan. Because there is little or no standardized terminology in qualitative data analysis, it is important to include a precise description as well as references to the works that describe the method intended (e.g., domain analysis as described by Spradley 1979 ; or grounded theory by means of constant-comparison as described by Boeije 2009 ).

2.4 Integration

To benefit optimally from the research being interdisciplinary the modules need to be brought together in the integration stage. The modules may be mono- or interdisciplinary and may rely on quantitative, qualitative or mixed methods approaches. So the MIR framework fits the view that distinguishes three multimethods approaches (quali–quali, quanti–quanti, and quali–quant).

Although the MIR framework has not been designed with the intention to promote mixed methods research, it is suitable for the design of mixed methods research as the kind of research that calls for both quantitative and qualitative components (Creswell and Piano Clark 2011 ). Indeed, just like the pioneers in mixed methods research (Creswell and Piano Clark 2011 : p. 2), the MIR framework deconstructs the package deals of paradigm and data to be collected. The synthesis of the different mono or interdisciplinary modules may benefit from research done on “the unique challenges and possibilities of integration of qualitative and quantitative approaches” (Fetters and Molina-Azorin 2017 : p. 5). We distinguish (sub) sets of modules being designed as convergent, sequential or embedded (adapted from mixed methods design e.g., Creswell and Piano Clark 2011 : pp. 69–70). Convergent modules, whether mono or interdisciplinary, may be done parallel and are integrated after completion. Sequential modules are done after one another and the first modules inform the latter ones (this includes transformative and multiphase mixed methods design). Embedded modules are intertwined. Here, modules depend on one another for data collection and analysis, and synthesis may be planned both during and after completion of the embedded modules.

2.5 Scientific quality and ethical considerations in the design of interdisciplinary research

A minimum set of jargon related to the assessment of scientific quality of research (e.g., triangulation, validity, reliability, saturation, etc.) can be found scattered in Fig.  1 . Some terms are reserved by particular paradigms, others may be seen in several paradigms with more or less subtle differences in meaning. In the latter case, it is important that team members are prepared to explain and share ownership of the term and respect the different meanings. By paying explicit attention to the quality concepts, researchers from different disciplines learn to appreciate each other’s concerns for good quality research and recognize commonalities. For example, the team may discuss measurement validity of both a standardized quantitative instrument and that of an interview and discover that the calibration of the machine serves a similar purpose as the confirmation of the guarantee of anonymity at the start of an interview.

Throughout the process of research design, ethics require explicit discussion among all stakeholders in the project. Ethical issues run through all components in the MIR framework in Fig.  1 . Where social and medical scientists may be more sensitive to ethical issues related to humans (e.g., the 1979 Belmont Report criteria of beneficence, justice, and respect), others may be more sensitive to issues related to animal welfare, ecology, legislation, the funding agency (e.g., implications for policy), data and information sharing (e.g., open access publishing), sloppy research practices, or long term consequences of the research. This is why ethics are an issue for the entire interdisciplinary team and cannot be discussed on project module level only.

3 The MIR framework in practice: two examples

3.1 teaching research methodology to heterogeneous groups of students, 3.1.1 institutional context and background of the mir framework.

Wageningen University and Research (WUR) advocates in its teaching and research an interdisciplinary approach to the study of global issues related to the motto “To explore the potential of nature to improve the quality of life.” Wageningen University’s student population is multidisciplinary and international (e.g., Tobi and Kampen 2013 ). Traditionally, this challenge of diversity in one classroom is met by covering a width of methodological topics and examples from different disciplines. However, when students of various programmes received methodological education in mixed classes, students of some disciplines would regard with disinterest or even disdain methods and techniques of the other disciplines. Different disciplines, especially from the qualitative respectively quantitative tradition in the social sciences (Onwuegbuzie and Leech 2005 : p. 273), claim certain study designs, methods of data collection and analysis as their territory, a claim reflected in many textbooks. We found that students from a qualitative tradition would not be interested, and would not even study, content like the design of experiments and quantitative data collection; and students from a quantitative tradition would ignore case study design and qualitative data collection. These students assumed they didn’t need any knowledge about ‘the other tradition’ for their future careers, despite the call for interdisciplinarity.

To enhance interdisciplinarity, WUR provides an MSc course mandatory for most students, in which multi-disciplinary teams do research for a commissioner. Students reported difficulties similar to the ones found in the literature: miscommunication due to talking different scientific languages and feelings of distrust and disrespect due to prejudice. This suggested that research methodology courses ought help prepare for interdisciplinary collaboration by introducing a single methodological framework that 1) creates sensitivity to the pros and challenges of interdisciplinary research by means of a common vocabulary and fosters respect for other disciplines, 2) starts from the research questions as pivotal in decision making on research methods instead of tradition or ontology, and 3) allows available methodologies and methods to be potentially applicable to any scientific research problem.

3.1.2 Teaching with MIR—the conceptual framework

As a first step, we replaced textbooks by ones refusing the idea that any scientific tradition has exclusive ownership of any methodological approach or method. The MIR framework further guides our methodology teaching in two ways. First, it presents a logical sequence of topics (first conceptual design, then technical design; first research question(s) or hypotheses, then study design; etc.). Second, it allows for a conceptual separation of topics (e.g., study design from instrument design). Educational programmes at Wageningen University and Research consistently stress the vital importance of good research design. In fact, 50% of the mark in most BSc and MSc courses in research methodology is based on the assessment of a research proposal that students design in small (2-4 students) and heterogeneous (discipline, gender and nationality) groups. The research proposal must describe a project which can be executed in practice, and which limitations (measurement, internal, and external validity) are carefully discussed.

Groups start by selecting a general research topic. They discuss together previously attained courses from a range of programs to identify personal and group interests, with the aim to reach an initial research objective and a general research question as input for the conceptual design. Often, their initial research objective and research question are too broad to be researchable (e.g., Kumar 2014 : p. 64; Adler and Clark 2011 : p. 71). In plenary sessions, the (basics of) critical assessment of empirical research papers is taught with special attention to the ‘what’ and ‘why’ section of research papers. During tutorials students generate research questions until the group agrees on a research objective, with one general research question that consists of a small set of specific research questions. Each of the specific research questions may stem from a different discipline, whereas answering the general research question requires integrating the answers to all specific research questions.

The group then identifies the key concepts in their research questions, while exchanging thoughts on possible attributes based on what they have learnt from previous courses (theories) and literature. When doing so they may judge the research question as too broad, in which case they will turn to the question strategies toolbox again. Once they agree on the formulation of the research questions and the choice of concepts, tasks are divided. In general, each student turns to the literature he/she is most familiar with or interested in, for the operationalization of the concept into measurable attributes and writes a paragraph or two about it. In the next meeting, the groups read and discuss the input and decide on the set-up and division of tasks with respect to the technical design.

3.1.3 Teaching with MIR—the technical framework

The technical part of research design distinguishes between study design, instrument design, sampling design, and the data analysis plan. In class, we first present students with a range of study designs (cross sectional, experimental, etc.). Student groups select an appropriate study design by comparing the demands made by the research questions with criteria for internal validity. When a (specific) research question calls for a study design that is not seen as practically feasible or ethically possible, they will rephrase the research question until the demands of the research question tally with the characteristics of at least one ethical, feasible and internally valid study design.

While following plenary sessions during which different random and non-random sampling or selection strategies are taught, groups start working on their sampling design. The groups make two decisions informed by their research question: the population(s) of research units, and the requirements of the sampling strategy for each population. Like many other aspects in research design, this can be an iterative process. For example, suppose the research question mentioned “local policy makers,” which is too vague for a sampling design. Then the decision may be to limit the study to “policy makers at the municipality level in the Netherlands” and adapt the general and the specific research questions accordingly. Next, the group identifies whether a sample design needs to focus on diversity (e.g., when the objective is to make an inventory of possible local policies), representativeness (e.g., when the objective is to estimate prevalence of types of local policies), or people with particular information (e.g., when the objective is to study people having experience with a given local policy). When a sample has to representative, the students must produce an assessment of external validity, whereas when the aim is to map diversity the students must discuss possible ways of source triangulation. Finally, in conjunction with the data analysis plan, students decide on the sample size and/or the saturation criteria.

When the group has agreed on their population(s) and the strategy for recruiting research units, the next step is to finalize the technical aspects of operationalisation i.e. addressing the issue of exactly how information will be extracted from the research units. Depending on what is practically feasible qua measurement, the choice of a data collection instrument may be a standardised (e.g., a spectrograph, a questionnaire) or less standardised (e.g., semi-structured interviews, visual inspection) one. The students have to discuss the possibilities of method triangulation, and explain the possible weaknesses of their data collection plan in terms of measurement validity and reliability.

3.1.4 Recent developments

Presently little attention is payed to the data analysis plan, procedures for synthesis and reporting because the programmes differ on their offer in data analysis courses, and because execution of the research is not part of the BSc and MSc methodology courses. Recently, we have designed one course for an interdisciplinary BSc program in which the research question is put central in learning and deciding on statistics and qualitative data analysis. Nonetheless, during the past years the number of methodology courses for graduate students that supported the MIR framework have been expanded, e.g., a course “From Topic to Proposal”; separate training modules on questionnaire construction, interviewing, and observation; and optional courses on quantitative and qualitative data analysis. These courses are open to (and attended by) PhD students regardless of their program. In Flanders (Belgium), the Flemish Training Network for Statistics and Methodology (FLAMES) has for the last four years successfully applied the approach outlined in Fig.  1 in its courses for research design and data collection methods. The division of the research process in terms of a conceptual design, technical design, operationalisation, analysis plan, and sampling plan, has proved to be appealing for students of disciplines ranging from linguistics to bioengineering.

3.2 Researching with MIR: noise reducing asphalt layers and quality of life

3.2.1 research objective and research question.

This example of the application of the MIR framework comes from a study about the effects of “noise reducing asphalt layers” on the quality of life (Vuye et al. 2016 ), a project commissioned by the City of Antwerp in 2015 and executed by a multidisciplinary research team of Antwerp University (Belgium). The principal researcher was an engineer from the Faculty of Applied Engineering (dept. Construction), supported by two researchers from the Faculty of Medicine and Health Sciences (dept. of Epidemiology and Social Statistics), one with a background in qualitative and one with a background in quantitative research methods. A number of meetings were held where the research team and the commissioners discussed the research objective (the ‘what’ and ‘why’).The research objective was in part dictated by the European Noise Directive 2002/49/EC, which forces all EU member states to draft noise action plans, and the challenge in this study was to produce evidence of a link between the acoustic and mechanical properties of different types of asphalt, and the quality of life of people living in the vicinity of the treated roads. While there was literature available about the effects of road surface on sound, and other studies had studied the link between noise and health, no study was found that produced evidence simultaneously about noise levels of roads and quality of life. The team therefore decided to test the hypothesis that traffic noise reduction has a beneficial effect on the quality of life of people into the central research. The general research question was, “to what extent does the placing of noise reducing asphalt layers increase the quality of life of the residents?”

3.2.2 Study design

In order to test the effect of types of asphalt, initially a pretest–posttest experiment was designed, which was expanded by several added experimental (change of road surface) and control (no change of road surface) groups. The research team gradually became aware that quality of life may not be instantly affected by lower noise levels, and that a time lag is involved. A second posttest aimed to follow up on this effect although it could only be implemented in a selection of experimental sites.

3.2.3 Instrument selection and design

Sound pressure levels were measured by an ISO-standardized procedure called the Statistical Pass-By (SPB) method. A detailed description of the method is in Vuye et al. ( 2016 ). No such objective procedure is available for measuring quality of life, which can only be assessed by self-reports of the residents. Some time was needed for the research team to accept that measuring a multidimensional concept like quality of life is more complicated than just having people rate their “quality of life” on a 10 point scale. For instance, questions had to be phrased in a way that gave not away the purpose of the research (Hawthorne effect), leading to the inclusion of questions about more nuisances than traffic noise alone. This led to the design of a self-administered questionnaire, with questions of Flanders Survey on Living Environment (Departement Leefmilieu, Natuur & Energie 2013 ) appended by new questions. Among other things, the questionnaire probed for experienced nuisance by sound, quality of sleep, effort to concentrate, effort to have a conversation inside or outside the home, physical complaints such as headaches, etc.

3.2.4 Sampling design

The selected sites needed to accommodate both types of measurements: that of noise from traffic and quality of life of residents. This was a complicating factor that required several rounds of deliberation. While countrywide only certain roads were available for changing the road surface, these roads had to be mutually comparable in terms of the composition of the population, type of residential area (e.g., reports from the top floor of a tall apartment building cannot be compared to those at ground level), average volume of traffic, vicinity of hospitals, railroads and airports, etc. At the level of roads therefore, targeted sampling was applied, whereas at the level of residents the aim was to realize a census of all households within a given perimeter from the treated road surfaces. Considerations about the reliability of applied instruments were guiding decisions with respect to sampling. While the measurements of the SPB method were sufficiently reliable to allow for relatively few measurements, the questionnaire suffered from considerable nonresponse which hampered statistical power. It was therefore decided to increase the power of the study by adding control groups in areas where the road surface was not replaced. This way, detecting an effect of the intervention did not solely depend on the turnout of the pre and the post-test.

3.2.5 Data analysis plan

The statistical analysis had to account for the fact that data were collected at two different levels: the level of the residents filling out the questionnaires, and the level of the roads which surface was changed. Because survey participation was confidential, results of the pre- and posttest could only be compared at aggregate (street) level. The analysis had to control for confounding variables (e.g., sample composition, variety in traffic volume, etc.), experimental factors (varieties in experimental conditions, and controls), and non-normal dependent variables. The statistical model appropriate for analysis of such data is a Generalised Linear Mixed Model.

3.2.6 Execution

Data were collected during the course of 2015, 2016 and 2017 and are awaiting final analysis in Spring 2017. Intermediate analyses resulted in several MSc theses, conference presentations, and working papers that reported on parts of the research.

4 Discussion

In this paper we presented the Methodology in Interdisciplinary Research framework that we developed over the past decade building on our experience as lecturers, consultants and researchers. The MIR framework recognizes research methodology and methods as important content in the critical factor skills and competences. It approaches research and collaboration as a process that needs to be designed with the sole purpose to answer the general research question. For the conceptual design the team members have to discuss and agree on the objective of their communal efforts without squeezing it into one single discipline and, thus, ignoring complexity. The specific research questions, when formulated, contribute to (self) respect in collaboration as they represent and stand witness of the need for interdisciplinarity. In the technical design, different parts were distinguished to stimulate researchers to think and design research out of their respective disciplinary boxes and consider, for example, an experimental design with qualitative data collection, or a case study design based on quantitative information.

In our teaching and consultancy, we first developed a MIR framework for social sciences, economics, health and environmental sciences interdisciplinarity. It was challenged to include research in the design discipline of landscape architecture. What characterizes research in landscape architecture and other design principles, is that the design product as well as the design process may be the object of study. Lenzholder et al. ( 2017 ) therefore distinguish three kinds of research in landscape architecture. The first kind, “Research into design” studies the design product post hoc and the MIR framework suits the interdisciplinary study of such a product. In contrast, “Research for design” generates knowledge that feeds into the noun and the verb ‘design’, which means it precedes the design(ing). The third kind, Research through Design(ing) employs designing as a research method. At first, just like Deming and Swaffield ( 2011 ), we were a bit skeptical about “designing” as a research method. Lenzholder et al. ( 2017 ) pose that the meaning of research through design has evolved through a (neo)positivist, constructivist and transformative paradigm to include a pragmatic stance that resembles the pragmatic stance assumed in the MIR framework. We learned that, because landscape architecture is such an interdisciplinary field, the process approach and the distinction between a conceptual and technical research design was considered very helpful and embraced by researchers in landscape architecture (Tobi and van den Brink 2017 ).

Mixed methods research (MMR) has been considered to study topics as diverse as education (e.g., Powell et al. 2008 ), environmental management (e.g., Molina-Azorin and Lopez-Gamero 2016 ), health psychology (e.g., Bishop 2015 ) and information systems (e.g., Venkatesh et al. 2013 ). Nonetheless, the MIR framework is the first to put MMR in the context of integrating disciplines beyond social inquiry (Greene 2008 ). The splitting of the research into modules stimulates the identification and recognition of the contribution of both distinct and collaborating disciplines irrespective of whether they contribute qualitative and/or quantitative research in the interdisciplinary research design. As mentioned in Sect.  2.4 the integration of the different research modules in one interdisciplinary project design may follow one of the mixed methods designs. For example, we witnessed at several occasions the integration of social and health sciences in interdisciplinary teams opting for sequential modules in a sequential exploratory mixed methods fashion (e.g., Adamson 2005 : 234). In sustainability science research, we have seen the design of concurrent modules for a concurrent nested mixed methods strategy (ibid) in research integrating the social and natural sciences and economics.

The limitations of the MIR framework are those of any kind of collaboration: it cannot work wonders in the absence of awareness of the necessity and it requires the willingness to work, learn, and research together. We developed MIR framework in and alongside our own teaching, consultancy and research, it has not been formally evaluated and compared in an experiment with teaching, consultancy and research with, for example, the regulative cycle for problem solving (van Strien 1986 ), or the wheel of science from Babbie ( 2013 ). In fact, although we wrote “developed” in the previous sentence, we are fully aware of the need to further develop and refine the framework as is.

The importance of the MIR framework lies in the complex, multifaceted nature of issues like sustainability, food security and one world health. For progress in the study of these pressing issues the understanding, construction and quality of interdisciplinary portfolio measurements (Tobi 2014 ) are pivotal and require further study as well as procedures facilitating the integration across different disciplines.

Another important strain of further research relates to the continuum of Responsible Conduct of Research (RCR), Questionable Research Practices (QRP), and deliberate misconduct (Steneck 2006 ). QRP includes failing to report all of a study’s conditions, stopping collecting data earlier than planned because one found the result one had been looking for, etc. (e.g., John et al. 2012 ; Simmons et al. 2011 ; Kampen and Tamás 2014 ). A meta-analysis on selfreports obtained through surveys revealed that about 2% of researchers had admitted to research misconduct at least once, whereas up to 33% admitted to QRPs (Fanelli 2009 ). While the frequency of QRPs may easily eclipse that of deliberate fraud (John et al. 2012 ) these practices have received less attention than deliberate misconduct. Claimed research findings may often be accurate measures of the prevailing biases and methodological rigor in a research field (Fanelli and Ioannidis 2013 ; Fanelli 2010 ). If research misconduct and QRP are to be understood then the disciplinary context must be grasped as a locus of both legitimate and illegitimate activity (Fox 1990 ). It would be valuable to investigate how working in interdisciplinary teams and, consequently, exposure to other standards of QRP and RCR influence research integrity as the appropriate research behavior from the perspective of different professional standards (Steneck 2006 : p. 56). These differences in scientific cultures concern criteria for quality in design and execution of research, reporting (e.g., criteria for authorship of a paper, preferred publication outlets, citation practices, etc.), archiving and sharing of data, and so on.

Other strains of research include interdisciplinary collaboration and negotiation, where we expect contributions from the “science of team science” (Falk-Krzesinski et al. 2010 ); and compatibility of the MIR framework with new research paradigms such as “inclusive research” (a mode of research involving people with intellectual disabilities as more than just objects of research; e.g., Walmsley and Johnson 2003 ). Because of the complexity and novelty of inclusive health research a consensus statement was developed on how to conduct health research inclusively (Frankena et al., under review). The eight attributes of inclusive health research identified may also be taken as guiding attributes in the design of inclusive research according to the MIR framework. For starters, there is the possibility of inclusiveness in the conceptual framework, particularly in determining research objectives, and in discussing possible theoretical frameworks with team members with an intellectual disability which Frankena et al. labelled the “Designing the study” attribute. There are also opportunities for inclusiveness in the technical design, and in execution. For example, the inclusiveness attribute “generating data” overlaps with the operationalization and measurement instrument design/selection and the attribute “analyzing data” aligns with the data analysis plan in the technical design.

On a final note, we hope to have aroused the reader’s interest in, and to have demonstrated the need for, a methodology for interdisciplinary research design. We further hope that the MIR framework proposed and explained in this article helps those involved in designing an interdisciplinary research project to get a clearer view of the various processes that must be secured during the project’s design and execution. And we look forward to further collaboration with scientists from all cultures to contribute to improving the MIR framework and make interdisciplinary collaborations successful.

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Acknowledgements

The MIR framework is the result of many discussions with students, researchers and colleagues, with special thanks to Peter Tamás, Jennifer Barrett, Loes Maas, Giel Dik, Ruud Zaalberg, Jurian Meijering, Vanessa Torres van Grinsven, Matthijs Brink, Gerda Casimir, and, last but not least, Jenneken Naaldenberg.

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Tobi, H., Kampen, J.K. Research design: the methodology for interdisciplinary research framework. Qual Quant 52 , 1209–1225 (2018). https://doi.org/10.1007/s11135-017-0513-8

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Multidisciplinary Teaching

Teaching across disciplines can take many forms, from a single educator incorporating outside material into their own teaching, to invited guest speakers or team-teaching experiences, to total-course collaborations between educators from different fields. Many educators find “teaching at the crossroads” an energizing and creative experience, and multidisciplinary teaching helps students learn how to tackle today’s complex problems.

What’s the research?

Hardy et al. (2021) argue that multidisciplinary, interdisciplinary, and transdisciplinary teaching approaches can generate positive cognitive and emotional outcomes for students, as well as help them develop critical thinking skills and a broad knowledge base that makes them more well-rounded and adaptable. They further propose that learners like this are needed to work on “complex, authentic problems with real-world importance” (Hardy et al., 2021, p. 1126).

To clarify differences among the approaches, Stember (1991) described:   

• Multidisciplinary work, in which people from different disciplines work together, each drawing on their disciplinary knowledge;
• Interdisciplinary work, which integrates knowledge and methods from different disciplines, using a real synthesis of approaches; and
• Transdisciplinary work, which involves understanding the unity of intellectual frameworks beyond the disciplinary perspectives.

While these differences are important logistically and pedagogically, Hardy et al. refer to multidisciplinary, interdisciplinary, and transdisciplinary teaching collectively as MITT, to differentiate them from single-discipline approaches and emphasize the potential for integrative learning that they all share.

Write a MITT-related learning objective . Explicitly state how you want learners to use material from across disciplines.  Some examples adapted from Golding (2009) include:

• Apply different disciplinary perspectives to modern-day events
• Employ multiple ways of knowing in problem-solving discussion
• Critically evaluate knowledge from a range of disciplines
• Synthesize knowledge from multiple disciplines to produce something greater than would be possible from any one disciplinary perspective

Assess for grounding, integration, and self-critique . Mansilla and Daraising (2007) recommend that assessment of student work across disciplines should include assessment of:

• How well pieces of the work are grounded in the discipline(s) upon which they draw;
• How well that work contributes to integrated insights and understandings (for example, conceptual frameworks, graphic representations, models, metaphors, or more comprehensive work); and
• The degree to which the work exhibits “a clear sense of purpose, reflectiveness, and self-critiqu e” (p. 222, emphasis added). Working with many disciplines involves different ways of knowing about something, so it is a natural opportunity to invite the learner to reflect upon the limits of various kinds of knowing—including their own.

Activities to stimulate MITT-related thinking with your students    

• Assign a “one minute paper” in which students take one minute to describe the connections, alignments, and divergences they see between material in your course and other courses they have taken. Conversation about these one-minute papers will help students deepen their understanding of your material.   
• Assign case studies on current events to student groups. Give groups a few primary sources like news articles, op-eds, or podcasts, and invite them to find more. Ask groups to identify the key problems in the case study—in both technical and human terms—and what research questions would help them understand or address those problems. Help groups find at least one expert to interview before they present to the class on the case, its problems, and their position(s) on its associated issues (Katy Shorey, Department of Philosophy and Religion, Northeastern University).   
• Create an assignment in which students explore the importance and relevance of a specific skill in multiple contexts. For example, you can begin by identifying a skill that’s central to your own course. Then ask students to work in groups to identify and research other contexts and disciplines where that skill is also a core skill—as many as they can (e.g., Hutchison, 2016).   
• Use student portfolios (or ePortfolios) to create a place for students to organize, reflect upon, and integrate different kinds of work (Peet et al., 2011; Peet, 2010).   
• Connect with colleagues from other disciplines interested in working together by joining a CATLR cohort program , teaching an interdisciplinary Honors seminar , leading a Dialogue of Civilizations, or connecting with an interdisciplinary research cluster .

References:

Golding, C. (2009). Integrating the disciplines: Successful interdisciplinary subjects . Melbourne, Australia: Centre for the Study of Higher Education.  https://educationnorthwest.org/sites/default/files/resources/trauma-informed-practices-postsecondary-508.pdf

Hardy, J. G., Sdepanian, S., Stowell, A. F., Aljohani, A. D., Allen, M. J., Anwar, A., Barton, D., Baum, J. V., Bird, D., Blaney, A., Brewster, L., Cheneler, D., Efremova, O., Entwistle, M., Esfahani, R. N., Firlak, M., Foito, A., Forciniti, L., Geissler, S. A., … Wright, K. L. (2021). Potential for chemistry in multidisciplinary, interdisciplinary, and transdisciplinary teaching activities in higher education. Journal of Chemical Education, 98 (4), 1124-1145. https://doi.org/10.1021/acs.jchemed.0c01363

Hutchison, M. (2016). The empathy project: Using a project-based learning assignment to increase first-year college students’ comfort with interdisciplinarity. Interdisciplinary Journal of Problem-Based Learning, 10 (1), 9. https://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1580&context=ijpbl

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• Research article
• Open access
• Published: 13 June 2018

Multidisciplinary teams and ICT: a qualitative study exploring the use of technology and its impact on multidisciplinary team meetings

• Anna Janssen   ORCID: orcid.org/0000-0001-6611-9651 1 , 2 ,
• Tracy Robinson 2 , 3 ,
• Melissa Brunner 1 , 4 ,
• Paul Harnett 5 ,
• Kylie E. Museth 5 &
• Tim Shaw 1 , 2  

BMC Health Services Research volume  18 , Article number:  444 ( 2018 ) Cite this article

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Multidisciplinary teams (MDTs) are an integral component in the delivery of health care. This is particularly evident in the delivery of cancer care, where multidisciplinary teams are internationally recognized as the preferred method for service delivery. The use of health information systems and technology are key enabling factors for building the capacity of MDTs to engage in improvement and implementation projects but there is scant research on how MDTs make use of technology and information systems or the kinds of systems needed for them to undertake improvement and implementation research. This paper reports findings on how seven MDTs in cancer care utilized technological and information systems and the barriers and enabling factors that impacted on their uptake.

Seven multidisciplinary teams from two large metropolitan hospitals participated in the study. Qualitative methods including structured observations and semi structured interviews that explored how teams engaged in research and improvement activities were utilized. Participants were also observed and interviewed in relation to their use of data and health information systems. Findings were subject to content analysis and key themes were identified. Interviews were transcribed and de-identified and key themes were subsequently discussed with participants to allow for member checking and further clarification of findings.

A total of 43 MDT meetings across seven tumor streams were observed. Of these, observation notes from 13 meetings contained direct references to emerging technologies and health information systems. Findings from 15 semi-structured interviews were also analyzed in relation to how MDTs used technology in weekly meetings, and the perceived impact of technology. Three broad themes emerged: (1) methods for data collection and use by MDTs, (2) the impact of technology on the MDT meeting environment, and (3) the impact of technology and information systems on clinical decision making.

The study demonstrates that real time data collection and imaging may improve patient centered care coordination. However, ICTs can be used sub-optimally by teams. We therefore urge additional research to identify the enabling factors that support better collection and use of outcome data from ICT.

Peer Review reports

An increasing body of literature is focused on investigating how existing and emerging information communication technologies (ICT) are impacting the health sector, both for patients and health care professionals. The literature reveals ICT is rapidly changing the way individuals engage with their own health [ 1 ]. Additionally, research shows ICT is improving clinical processes by supporting data-driven care and allows patient outcomes to be measured and compared to benchmark performance metrics [ 2 ]. Finally, the contemporary data revolution transforming the health sector is being driven by improvements in ICTs [ 3 ]. This is because advances in technology make health data accessible and actionable, enabling clinicians to change their practices [ 4 ]. It is clear from the literature that the widespread use of existing and emerging technologies are reshaping healthcare. However, there are notable gaps in understanding how technology can be used to better understand the patient experience and how technology in areas such as cancer care can be utilized to improve patient-centered models of care. There is a recognized lack of understanding of how ICTs can be used to support the delivery of quality care for patients, and enable linkages across different applications and data sets [ 5 ]. Furthermore, the literature that uptake of ICT in the health sector is more common when the functionality of the technology offers financial benefits, then whether they offer quality or safety benefits [ 6 ].

A decade ago it was identified in the literature that ICT systems could be of benefit in health care due to their capacity to capture rich patient data and support standardization of care [ 6 ]. In addition, real time decision support for oncologists and service users, has the potential to significantly improve clinical outcomes [ 7 ]. Despite a consensus that the use of ICT systems should lead to more efficient and high quality care [ 8 ] the integration of these systems into cancer services has been slow and uneven. Overall, there is a paucity of literature that addresses how technology can be integrated effectively into cancer care. One significant barrier to the successful implementation of ICT is the perception that newer systems such as electronic medical records and databases offer no significant improvement over existing approaches such as paper-based notes, and in many instances may increase the workload of clinical staff [ 9 ]. Other cited challenges include questions about the security and reliability of web based information, uneven access to online facilities and a lack of operator skills among health workers [ 6 ]. There is evidence in the literature demonstrating that ICT can be used to improve data collection, but this is often limited to specific medical disciplines such as surgery [ 10 ]. However, there is also evidence to suggest that poorly implemented ICT in healthcare can contribute to the wide scale collection of poor quality data [ 11 ]. One of the major challenges to overcome in the implementation of ICT for data collection is improving linkages between systems and data access issues [ 12 ]. In addition to this, despite collecting a plethora of performance indicator data, meaningful measures of patient experience, equity and population health outcomes remain elusive [ 13 ]. The use of ICTs in cancer care is an important issue, which warrants further exploration.

A core component in the delivery of cancer care is the use of multidisciplinary teams (MDTs). The central function of MDT meetings is to bring together a team of health care professionals to determine a patient’s treatment plan [ 14 ]. MDT meetings are widely used in the health care sector and in the UK they have been recognized at a policy level as the preferred means of delivering care [ 15 ]. MDTs are not just central to the delivery of cancer care, but are a central component in the delivery of healthcare more generally. This is particularly evident in the literature on the benefits of multidisciplinary care to create links between specialists and primary care providers [ 16 ]. The literature has demonstrated that team-based approaches to healthcare delivery can improve some aspects of the quality of care delivered to patients [ 17 ]. Furthermore, team-based care can benefit health professionals as well as patients, by improving understanding of patients care plans and overall professional climate [ 18 ].

Although MDTs are a central component of cancer care in many countries, there is a notable gap regarding how technology and information systems can be integrated into these teams. The lack of research into how ICTs can be integrated into MDTs is concerning considering the importance of well implemented ICTs on the coordination of care by health professionals [ 2 , 19 ]. The use of ICTs in the form of clinical dashboards and clinical decision support systems have also been shown to improve processes and patient outcomes for cardiovascular multidisciplinary teams [ 20 ]. Further, the literature has demonstrated ICTs used to facilitate multidisciplinary blood pressure management between treatment teams and patients can improve blood pressure management and control [ 21 ]. Finally, a recent review of the literature concluded that successful implementation of ICTs in multidisciplinary care has the capacity to enable universally accessible, cost-effective, and high quality care, particularly for patients in rural and remote locations [ 22 ].

In a previous paper, the authors reported findings from an ethnographic study on the engagement of MDTs in translational research and quality improvement [ 23 ]. One of the findings of this study was that the capture of real time data was a priority to help engage teams more actively in quality improvement activities [ 23 ]. There is also evidence in the literature that the use of specific ICTs, such as clinical support technologies, have potential to enhance a range of aspects of MDTs including operational and governance aspects [ 24 ]. However, effective use of innovations such as disruptive ICTs is more complex than just making them available, and also requires the use of additional solutions such as promotion of a culture of innovation in, access to real-world data and implementation of a whole-system approach to guide investment in innovation [ 25 ]. This highlights the need to better understand the use of ICT systems in cancer care and the specific capabilities needed to support integrated health information.

The current literature on the use of ICT in MDT meetings indicates its use varies according to a range of contextual factors, including the culture of MDTs and the meeting environment, that have been shown to have a significant impact on how effectively a team can use and access technology [ 26 ]. MDT meetings often take place in clinical spaces that are not built to facilitate interaction with technology and where the presentation of patient imaging is challenging and access to high-speed internet is not guaranteed [ 15 ]. There is very little research into the uptake and usage of ICTs in clinical teams like MDTs, and how they impact on team dynamics. Increasing understanding of the use of technologies is a key component in improving the implementation of current and future technologies to enhance the capacity of MDTs to lead healthcare improvement and innovation. This is particularly important in relation to the growing prevalence of ICT such as electronic medical records (EMRs) which are transforming the collection and redistribution of clinical data [ 8 ]. However, maximizing the use of EMR data by MDTs is not just about improving collection but understanding how teams can best make use of it to lead healthcare improvement and innovation.

The project described in this article was part of a wider research study, exploring the barriers and enabling factors that support research translation and implementation projects in oncology MDTs. This article presents findings on the specific use of ICTs in an MDT program of cancer care at two sites in Sydney. The primary objective of the study presented in this article was to identify how oncology MDTs currently used ICTs, and to explore how the use of these ICTs affected interactions within MDT meetings. The study was undertaken prior to the scheduled progressive roll out of Oncology Management Information Systems across Australian hospitals.

This paper reports secondary findings from an ethnographic study on the engagement and use of translational research and quality improvement by MDTs in cancer care [ 23 ]. Data were collected from unstructured observations and semi-structured interviews with members of seven MDT tumor stream meetings at two sites in Sydney in 2014. MDTs self-selected to participate in the study and included the following streams: Breast, Upper Gastrointestinal, Lower Gastrointestinal, Lung, Gynecological Oncology, Metastatic Breast, and Melanoma meetings.

Three researchers (TR, AJ, KM) conducted unstructured observations of participating MDTs over a period of 2 months. Each researcher took field notes during the MDT meetings and recorded their observations of the meetings. Analyses of observation notes involved identifying all references to the theme of health information systems and technology and how it was used. Comments were grouped according to broad themes that provided information on contextual factors such as how information systems were used in meetings and whether these systems supported treatment decisions.

At the conclusion of the observation period, semi-structured interviews were conducted with individual MDT members. The semi-structured interviews focused on exploring themes around the use of health information systems and technologies that had emerged from analysis of the observational notes, in order to explore them in more depth [ 27 ]. Semi-structured interviews took between 30 to 60 min and were conducted face-to-face. Refer to Additional file  1 to see the semi-structured interview schema. Interviews were recorded, transcribed, and de-identified. The interview transcripts underwent an initial reading to identify terms that indicated the use of technology or ICTs. The researchers discussed the terms in the text and agreed on how they could be grouped into broad categories. The researchers then discussed the context of keywords in the transcripts and reached a consensus regarding which broad category would be most appropriate for the keyword. These broad categories and keywords were translated into a reference table for use in subsequent readings, and structured categorisation of the transcripts. (Table  1 identifies broad categories identified by consensus and aligning key words). Subsequent readings of the transcripts were informed by the broad categories and keyword in the reference table, and enabled a structured review of the transcript to identify themes that were consistent across interviews [ 28 ].

Permission to conduct this study was granted by human research ethics committees of the University of Sydney, the local health district.

Results from structured observations

A total of 43 MDT meetings (MDTMs) were observed and their notes reviewed. Of these, a sub-set of notes from 13 MDTMs contained direct references to how the teams used technology and the impact its use had on the MDTM. Every location had facilities to project images onto a screen, as well as access to at least one computer. Some locations also had access to other technologies such as televisions, imaging equipment, teleconferencing facilities, lightboxes, and microscopes. Only two of the meetings had dedicated administrative support .

Irrespective of location, all meetings had an established seating routine, consisting of an inner and an outer circle of members. The small size of the room often reinforced this seating arrangement with a large table occupying most of the space. The inner circle consisted of senior clinicians including, oncologists, surgeons, radiologists, senior nursing staff and pathologists. The outer circle consisted of junior doctors and trainees, medical students, allied health, clinical trial nurses, and late attendees. The researchers observing the meeting also sat in the outer circle. The location of hardware dictated that imaging staff sat in the outer circle of the room. In MDTM rooms screens, microscopes, light boxers and desktop computers were located at the edges of the room, with a large table in the central space.

Overall, technology was most frequently used to display patient imaging. Screens at the front of the meeting room displayed patient scans and imaging experts reported their interpretation of the results. The display of patient imaging and scans was a clear facilitator of discussion across specialties, particularly between oncologists and pathologists. It was also often a source of discussion between the inner and outer circles of the meeting as more senior specialists asked questions of junior doctors seated in the outer circle in relation to treatment options and prognosis. In one MDT tumor stream meeting the chair regularly engaged junior doctors in the outer circle by asking them to conduct internet searches for literature to support certain diagnoses.

Challenges in relation to relying on imaging equipment were also evident. On occasions imaging or imaging reports were not available or older images could not be accessed to allow team members to assess disease progression. This was a result of poor access to patient databases or gaps in the available data. Imaging was observed to be unavailable due to either to the challenge of integrating digital systems or because results had not arrived from external imaging providers. A dedicated meeting coordinator was observed to play an important role ensuring timely access to imaging. This meeting coordinator ensured that agendas, patient lists and reminders were disseminated and this helped ensure all relevant results were available for the MDTM. At those meetings that had dedicated administrative support agendas, patient lists and reminders were disseminated and this helped ensure all relevant results were available.

One MDT used teleconferencing equipment to support a satellite MDT in a rural location. Despite having the capacity to link with rural areas this was generally only used as required or when requested by a clinician. Another MDT encouraged junior doctors to deliver a PowerPoint presentation of a clinical case study they had encountered for discussion with the team. This MDT also allowed time for research-focused members to present their research. Another MDTM chair encouraged registrars to regularly use smartphones to source information on treatment options and diagnosis. Only one team entered ‘real time’ data during the meeting and this was led by a registrar who was undertaking a local healthcare improvement project.

Overall, findings from observations confirmed the importance of imaging equipment to diagnose and discuss treatment options. The use of imaging impacted on the environment of meetings and stimulated team discussion. Only one team utilized information systems to enter ‘real time’ data and one used teleconferencing facilities.

Semi structured interview results

A total of 15 interview transcripts contained references to technology, how MDTs used technology in their weekly meetings, and key enabling factors for improved use of health information systems. Three broad themes emerged, including the use of technology for data collection, how environmental factors and the use of health technology in MDT meetings technology shapes the MDTM environment, and the impact of technology on clinical decision making. Table  2 contains exemplar quotes for these themes (Refer to Table 2 to review illustrative quotes categorized by theme ).

Theme 1: Data collection

Participants were unanimous that data collection was important and enabled by health information systems. Several also commented on the implementation of an EMR and stated that it would only be beneficial if it contained accurate, high quality data. They expressed concerns about the quality of data that was currently collected through MDTMs. One participant reported that patient-centered data such as quality of life was noticeably absent and that this was a significant gap in understanding how treatments affected patients and their discussions around end of life care.

Several barriers to the collection of quality data were identified, including that it was time consuming to collect, that there was duplication across multiple databases which could lead to errors, or that there was no one in the MDTM to collect the data. One participant felt that the quality of data collection varied across disciplines, as areas such as radiology and surgery had specific reporting requirements that effectively mandated the collection of specific data. Another noted that the collection of routine data such as length of stay or time between admissions was not indicative of treatment outcomes or quality of life. Ultimately, data collected from the MDTMs varied according to the skills of individual members and the resourcing of individual teams. Nevertheless, all participants identified that information systems should be used to collect high quality data and that MDTMs present a unique opportunity for improving data collection.

Participants also commented on the burgeoning number and duplication of databases and the challenges this posed in terms of data linkage and ownership of data. Two interviewees noted a reluctance by clinicians and researchers to share their data, which could reflect legal and confidentiality concerns. Reticence to share data was considered as a barrier to promoting evidence-based care. This kind of ‘territorial’ approach to data was also seen as one of the reasons for multiple and replicated databases. The proliferation of duplicate databases is problematic because they are usually unlinked and not contextualized within a larger body of either local or global population data.

Using innovative technologies such as linked databases that allowed real time data entry and analysis was considered challenging. It was reported that health information systems were not always implemented well and were poorly integrated into MDTMs. This, in turn, fueled resistance to new systems. The importance of time and support were highlighted to avoid data collection impacting on clinical workloads and most participants recommended more resourcing for MDTs in relation to this. In particular, funding for a dedicated data manager who understands the structure of clinical databases and who could attend MDTMs regularly was identified as a key enabling factor. Participants reported that ideally, the same person who collected the data would enter it into the database and suggested that the MDTM could be used as a quality control opportunity to review the data and ensure its accuracy. One disparate comment related to utilizing technology to feed data back to MDTMs and noted that this would allow clinicians to engage with their data and better identify quality gaps and improvement issues.

Theme 2: Environmental factors and the use of health technology in MDT meetings

A number of participants referred to cultural and environmental factors that influenced the use of information systems and imaging equipment within meetings. The ability to display and interpret patient scans relied on an appropriate meeting room and the attendance of specialists such as pathologists who have the ability to interpret the images. In one MDT, the pathologist did not always attend and delays occurred when their opinion was required. This highlights how the effective use of technology relies on both location and clinician expertise.

It was identified that common electronic tools had the capacity to shape and improve MDTMs. Digital tools such as PowerPoint slides were easily available to present patient case reviews at MDTMs, but were rarely used. The need to improve the MDT environment to create a vehicle for collecting good clinical data was discussed extensively as was the importance of having members with specialized knowledge such as programming to ensure the optimal use of technology. However, it was felt the current system made access to these experts difficult.

Theme 3: The impact of technology on organizational processes

Participants were unanimous that health information systems and imaging had an important role in supporting clinical decision making. This was supported by observations that confirmed the role of imaging in facilitating discussions about disease staging, treatment, and prognosis among team members. When patient scans were unavailable delays in treatment decisions occurred and one participant stated there was a need to identify which external imaging companies made scan results available online, and that patients should be referred to only those companies for their scans to ensure access to timely treatment. Timely access to imaging was crucial for helping to identify discrepancies in previous diagnoses and enhancing the ability to compare and discuss individual treatment plans. Additionally, all participants agreed that imaging technology and real time data supported and enhanced clinical discussion during meetings.

The findings from this study indicate that MDTs currently use a wide variety of ICT in support of and during their meetings. This aligns with the broader literature which indicates that there is widespread use of technology in the health sector and that it is transforming the delivery of care [ 1 , 2 ]. ICTs have great potential for improving aspects of healthcare, and they have been used in innovative ways in the health sector [ 3 ]. However evidence on the effectiveness of these innovations is lacking, and there are a range of challenges still to be overcome [ 24 , 29 ]. Findings from this study build on the existing literature by suggesting that MDTs currently do not make optimal use of health information systems and technology. There are several barriers to optimal use of ICT during MDT meetings including, physical environment, time, and ICT skills of individual team members. The barriers identified in this study are consistent with the perception that new technologies are burdensome and increase workloads [ 30 ].

Although this study focused broadly on the use of ICT in MDTs, participants identified the collection and use of real time clinical data as a priority. In addition, MDT leaders and champions expressed a desire to collect meaningful patient-centered data (such as quality of life) that could help inform treatment choices and end of life care. This is consistent with findings that acute and long term physical and psychosocial comorbidities are associated with cancer treatment, indicating there is an increasing need for supported self-management and shared care [ 9 ]. Furthermore, patient experience or patient reported outcome measures are an indicator of service quality [ 31 ]. MDTs have an important role in this process and if we are to improve treatment decisions and quality of care we need to identify the key outcomes and data relating to patient experience that can inform this process. Well implemented ICTs for data collection have the potential to improve the coordination of cancer care in MDTs, as they have been shown to do in other health areas [ 21 ].

Overall, participants felt ICT had the potential to make clinical data collection more accurate, and easier to feed back to MDTs for a range of applications. This finding aligns with clinical data research, which has shown that the increasing use of technologies such as electronic medical records has made data more accessible to clinicians by opening up opportunities to access their data for a range of uses from clinical processes to quality improvement [ 29 , 32 ]. At the same time, some participants expressed their concern that health services now collect a plethora of data but much of it lacks utility and accessibility. The literature has demonstrated that the widespread use of ICTs for clinical data collection has had the effect of collecting vast amounts of inaccurate or unnecessary data [ 11 ]. Findings from this study showed clinicians themselves are aware of the risk of collecting data that lacks value. Moving forward, the challenges in identifying which clinical data to collect may be overcome through the engagement of end-users, such as health professionals, in the design and implementation of data collection ICTs.

Although ICTs can facilitate the collection of unnecessary data, findings from this study indicated that technology has the potential to be an enabling factor in improving the collection of high quality clinical data, as it can make data input straightforward and easier to feed back to clinical teams. Technology that enabled efficient collection of clinical data was demonstrated by one participating MDT that used technology to incorporate ‘real time’ data collection into their meetings. Interviews with participants of this team identified that not only was this more efficient, but also the team collection of meaningful, patient-centered data was helpful for informing clinical decision making and end of life care. This aligns with previous research that identified ‘close to the source’ data increased the quality of data collection [ 30 ]. Hence, data collection may be considered a dimension of service quality and used as an indicator of quality. MDTs have an important role in this process and if we are to improve treatment decisions and follow up care we need to identify the key outcomes and data that can inform this process.

An integral part of this process will be ensuring that clinicians, themselves, see the value and feasibility of collecting patient-reported outcomes (PROMs). ICTs have the potential to integrate PROMs into routine data collection systems and more research into how this can be enabled in cancer care is imperative [ 33 ]. Indeed, there is an urgent need to identify a taxonomy of core PROM domains and dimensions in cancer because these are rarely implemented in clinical practice despite wide acknowledgement that it is crucial to capture the patient’s experience of treatment and care [ 31 ].

In spite of the interest in the use of ICTs to improve aspects of the MDT such as data collection, findings from this study suggest the use of ICT in and of itself is insufficient in changing team dynamics and improving the delivery of care. ICT on its own is a tool that can be harnessed to enhance MDTs, but there are also human and organizational factors that support successful use of technologies in health care. A particularly important one for MDTs is having access to specialists who understand how to use and interpret the technologies and information systems, such as experts who can design clinical databases for teams or analyze clinical data sets during meetings. Thus the successful implementation of health technologies may require task re-allocation in order to ensure relevant staff have adequate skills to use the technologies optimally [ 8 , 34 ]. Furthermore, complex technologies often require organizations to invest in individuals to ensure they possess skills with specific technologies in order to support their implementation in MDTs [ 35 ]. The need to upskill existing staff or engage staff with specialised ICT skills may increase costs for healthcare organisations in order to ensure ICT sustainability. Such an outcome stands at odds with much of the currently literature which champions ICTs as a cost-effective solution for improving the quality of healthcare [ 22 ].

Although the literature acknowledges the benefits of multidisciplinary care for both patients and health professionals, there are still gaps in understanding as to how best support this type of care [ 24 ]. This lack of understanding is coupled with the challenges of implementing innovations in MDTs, such as adequate uptake and cost-effectiveness [ 25 ]. Findings from this study indicate that in order to overcome implementation challenges for innovations such as ICT within MDTs it is important for both individuals and organizations to recognize when and how it can be used to benefit practice. This is particularly important in rapidly evolving areas such as the collection and feedback of data for both clinical and research purposes. Doing this effectively requires information technology experts, implementation researchers, and clinical teams to work together to develop implementation approaches for using ICT in a way that will lead to behavior change. Organizations will also need to acknowledge and support the need for resourcing in order to utilize emerging technologies in optimal ways.

Limitations

This research study asked two questions how MDTs use ICTs and how this impacted on interactions in meetings. In regards to answering the first question, the study is limited by the fact that it only represents the observations of MDT members at two sites, over a sampling of MDTMs. Given that the MDT members were aware they were being observed, it is possible they were affected by the Hawthorn effect. The Hawthorn effect states that all observational studies are vulnerable to the Hawthorn effect whereby participants alter their behavior in response to being observed. The researchers attempted to overcome this limitation by attending multiple meetings of each tumor stream over the course of the study, and attending a MDTMs across a broad range of tumour streams. It must also be acknowledged that data was collected through unstructured observations. As such, it is possible that only a small sub-set of observational notes recorded ICT use due to variation in what the observers recorded. Finally, the study observations focused on an area of practice that is experiencing rapid change: ICT usage, at a specific moment of time, as a result findings cannot be generalized across settings. Additionally, elements of ICT observed in the organisation when this study was undertaken may have changed during the publication process. In regards to answering the second question the study is limited by fact that it relied on consensus of researchers to identify categories and themes as such, categorisation of the data is potentially limited by the understanding of the researchers of the definitions of the categories and keywords.

The project reports on two phenomena in order to get a comprehensive picture on the use of ICTs in MDTs: 1) Interactions of MDTs and 2) the use of ICT by MDTs. As two phenomena are being observed, confounding factors make it difficult to draw clear conclusions as to which of the two phenomena are creating the result. However, confounding factors are a common barrier in implementation and health services research and it is still beneficial to observe the way ICTs may alter MDTM interactions.

Although the methodology used in this research project was beneficial for understanding how oncology MDTs currently used ICTs and how the use of these ICTs effected interactions within MDT meetings, alternatives could be adopted by future researchers. This could include focusing observations on an individual tumour stream to minimise variation of observations across specialties. Alternatively, researchers could observe MDT meetings during the same period (ie 4 weeks at the start of a calendar year) over multiple years to understand how ICT use is integrated and sustained over time.

The use of ICTs is commonplace in MDT meetings, particularly technologies for displaying patient imaging and other pertinent patient history information. However, ICTs continue to be underutilised for real time data collection and feedback, an application that is of particular use to health professionals. Improving real time data collection and feedback has the potential to improve quality, care coordination and patient-centered models of care. This potential is not always realized and there is value in identifying the enabling factors that support better collection and use of outcome data and other health information systems. Although there are a range of barriers to implementing ICT effectively in healthcare, there are also a number of factors that may increase the likelihood of successful integration. From an organisational perspective, it is important that adequate resourcing is provided so that MDTs have access to the right technologies at the right time and place. From the perspective of MDTs effective implementation of ICTs can involve engaging members who have the skills to use specific technologies optimally, so that technologies can be harnessed in a way that is synergistic with the existing structure of the MDTM.

Abbreviations

Cultural systems paradigm

Electronic medical record/s

Multidisciplinary team

Multidisciplinary team meeting

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Acknowledgements

The authors wish to acknowledge the Sydney West Translational Cancer Research Centre for their support of this study.

All authors listed in this publication conducted the research as part of the salaried position supported by their hiring organization. No additional funding was provided for this research study.

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Anna Janssen, Tracy Robinson & Tim Shaw

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Tracy Robinson

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Melissa Brunner

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AJ and TR made a substantial contribution to study design, data collection and data analysis, as well manuscript preparation. PH and TS made a substantial contribution to study design and manuscript preparation. KM made a substantial contribution to data collection and manuscript preparation. MB made a substantial contribution to manuscript preparation. All authors read and approved the final manuscript.

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Additional file 1:.

Semi structured interview schema. The semi-structured interview prompts used to inform the interviews with MDT members. (DOC 28 kb)

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Janssen, A., Robinson, T., Brunner, M. et al. Multidisciplinary teams and ICT: a qualitative study exploring the use of technology and its impact on multidisciplinary team meetings. BMC Health Serv Res 18 , 444 (2018). https://doi.org/10.1186/s12913-018-3242-3

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Medical School Expert

What Is A Multidisciplinary Team? (Healthcare MDTs Explained)

Every article is fact-checked by a medical professional. However, inaccuracies may still persist.

I think it was only after I started taking part in multidisciplinary team meetings as a doctor that I actually understood what they were and what value they could bring to patients.

A multidisciplinary team (MDT) in healthcare is a group of professionals from various disciplines who collaborate to provide comprehensive care for patients. These teams are designed to bring together the unique skills and expertise of each member, ultimately resulting in improved patient outcomes.

Through effective communication, collaboration, and coordinated planning, MDTs aim to deliver personalised and efficient care.

In the context of healthcare, MDTs typically include a range of professionals such as doctors, nurses, physiotherapists, occupational therapists, social workers, and other specialists.

Each member of the team contributes their specific knowledge and skills to develop a cohesive care plan tailored to the needs of the individual patient.

The collective approach allows MDTs to assess each case from multiple perspectives, enhancing the quality of care and preventing gaps in service provision.

Key Takeaways

• Multidisciplinary teams consist of various professionals working together to provide comprehensive care for patients with complex health needs.
• The diverse skills and knowledge within the team contribute to tailored care plans and improved patient outcomes.
• Collaboration within MDTs leads to integrated care, greater efficiency, and the sharing of best practices among healthcare professionals.

INCLUDED IN THIS GUIDE:

What Is A Multidisciplinary Team?

The concept of multidisciplinary care can be traced back to the early 20th century.

However, it became more prominent in the latter half of the century as healthcare began to recognise the complexity of patient needs, which often required a multifaceted approach.

As medicine evolved and specialisation increased, there was a growing realisation that no single professional had the breadth of expertise needed to address all aspects of patient care, especially for chronic or complex conditions.

In the 1970s and 1980s, MDTs gained significant traction in cancer care.

Recognising that cancer treatment often required surgeons, oncologists, radiologists, and other specialists to work together, many hospitals began organising tumour boards or multidisciplinary cancer conferences.

By the 1990s, the multidisciplinary approach started expanding beyond cancer care.

Fields such as rehabilitation, geriatrics, paediatrics, and mental health began to adopt this model to optimise patient outcomes.

Today, MDTs are a standard in many healthcare settings.

The collective expertise of an MDT often results in better diagnostic and treatment decisions, as professionals can discuss and debate the best course of action.

Who’s In A Multidisciplinary Team?

There’s no one set line-up for a multidisciplinary team in healthcare. Which professionals make up an MDT all depends on the setting and the patient’s needs.

Example Of A Hospital MDT

In a hospital setting, an MDT might consist of the following professionals:

• Doctors : A range of specialist doctors may be involved, such as surgeons, oncologists, cardiologists, or psychiatrists.
• Nurses : Specialist and general nurses play a pivotal role in the team, providing expert care and support to patients.
• Therapists : Therapists, such as physiotherapists, occupational therapists, and speech and language therapists, help patients with rehabilitation and recovery.
• Pharmacists : They provide advice on medication and ensure that patients receive the appropriate medications during their treatment.

Example Of A Community/GP MDT

In a community or general practice setting, an MDT might include the following professionals:

• General Practitioners (GPs) : They provide primary medical care and act as a patient’s first point of contact in the healthcare system.
• Nurses : Practice nurses offer a wide range of care services, including health promotion, immunisations, and management of long-term conditions.
• Pharmacists : Community pharmacists ensure patients receive the appropriate medication and can provide advice on managing various conditions.
• Social Workers : Social workers address the social needs of patients, such as housing, financial support, or care provision.

Who’s In Charge Of An MDT?

There’s rarely one set leader in an MDT- the leadership role may vary depending on the team’s structure and the setting.

In some cases, a senior clinician or specialist doctor may take charge, while in other instances, a nurse or therapist may lead the team.

Ultimately, the goal of the MDT is to deliver comprehensive, coordinated, and person-centred care for patients, and effective communication across disciplines is essential for achieving this.

What Do Multidisciplinary Teams Do?

MDTs play a vital role in ensuring that patients with different needs receive a seamless flow of care.

MDT meetings are typically held in a conference room or a dedicated space equipped with the necessary IT.

After a brief introduction, a particular patient’s case is presented, often by the responsible doctor or a designated member of the team familiar with the patient.

Essential details about the patient’s condition, history, diagnostic results, and current treatments are shared with the group.

As this information is presented, radiological images or lab results may be displayed on screens for everyone to review.

Once the case has been laid out, various team members contribute their insights, assessments, and recommendations.

For instance, a radiologist might interpret imaging results, a surgeon might discuss potential surgical interventions, and a nurse might provide input on the patient’s day-to-day well-being and response to treatments.

The discussion becomes an interactive session, with team members asking questions, offering suggestions, or raising concerns based on their expertise.

The objective is to reach a consensus on the best care plan for the patient, ensuring that all aspects of their health and well-being are considered.

After discussing a patient’s care, decisions are documented (in a doctor’s best handwriting), and tasks or action items are delegated to the appropriate team members.

The meeting progresses in this manner, with the team discussing multiple patients as time allows.

In addition to patient-specific discussions, MDT meetings might also address administrative issues, new protocols, or educational topics relevant to the team’s practice.

How often the team meets varies based on the hospital’s needs, type of hospital, and the complexity of cases. Some teams might meet daily, while others convene weekly or even monthly.

Benefits Of A Multidisciplinary Team

As I’ve somewhat touched on so far, there are some significant advantages to using an MDT approach in patient care.

Comprehensive Patient Care

By bringing together diverse expertise, these teams can provide more comprehensive care tailored to a patient’s unique condition.

This holistic approach ensures that all aspects of the patient’s wellbeing, including physical, mental, and social facets, are considered and addressed in their care plan.

Improved Communication

One of the key advantages of a multidisciplinary team is the improved communication between healthcare professionals.

When working together closely, team members can share information, insights, and resources more effectively.

This helps to ensure that everyone is on the same page regarding the patient’s care and that any decisions made are based on a collective understanding of the patient’s needs and progress.

• Better information sharing: Team members can quickly and easily share updates and important information with one another.
• Increased collaboration: Healthcare professionals have the opportunity to brainstorm and problem-solve together, leading to innovative solutions and a more cohesive approach to patient care.

Better Patient Outcomes

When healthcare professionals work as part of a multidisciplinary team, it generally improves outcomes for patients.

By providing a more coordinated and integrated approach to care, the team can identify and address potential issues before they escalate, helping to prevent complications and reduce the risk of poor treatment outcomes.

Additionally, patients with complex needs and long-term conditions typically benefit the most from this holistic care provision.

Challenges Of Multidisciplinary Team Working

While they generally do work well, it would be wrong to assume there aren’t any challenges associated with using a multidisciplinary team.

Hierarchy And Power Dynamics

The reality is that hierarchy and power dynamics can pose significant challenges to smooth team working.

Psychological barriers caused by professional silos, grades of doctors, and power differentials can hinder team performance and collaboration.

These dynamics can cause conflicts and undermine the sharing of information and decision-making processes.

Coordination Challenges

Coordination is another challenge faced by multidisciplinary teams in healthcare.

As the teams consist of individuals from different disciplines, each with their own schedules and departments, getting everyone together in one room isn’t always that easy.

Furthermore, organisational barriers, such as distributed teams and hybrid working models, can make it even more challenging to coordinate efforts and ensure the smooth functioning of the team.

Differing Professional Priorities

Multidisciplinary teams in healthcare often face challenges related to differing professional priorities among team members.

Each discipline may have its own priorities, goals, and practices, which can sometimes lead to disagreements and conflicts within the team.

These disagreements can make it difficult for the team to come together and work towards a common goal, potentially impacting the quality of patient care provided.

MDT Case Study

For this final section, I thought it could be useful to look at a case study of how an MDT would work together to care for a patient admitted to hospital with a broken hip.

Upon admission, the nursing staff would assess the patient’s immediate needs and manage their pain.

They would provide bedside care and communicate any concerns to the rest of the MDT.

Meanwhile, a radiologist would evaluate X-rays and other imaging results to determine the severity of the fracture and inform the team about the type of injury.

The orthopaedic surgeon would then review the imaging results and determine the best course of action for repair, whether it be surgery or a non-surgical intervention.

The surgeon would discuss their recommendations with the rest of the MDT, ensuring all members are informed and can contribute their expertise to the decision-making process.

The physiotherapist would also be involved in the patient’s care, providing guidance on mobility and developing a rehabilitation plan to help the patient regain strength and function after the injury.

The occupational therapist would assess the patient’s home environment and suggest adaptations to promote independence and safety during recovery.

Depending on the patient’s overall health and any pre-existing conditions, additional specialists, such as a geriatrician, may be included in the MDT to manage other concerns and optimise the patient’s health throughout their hospital stay.

The pharmacist would ensure that medications are appropriate for the patient and coordinate with other team members to manage potential drug interactions.

Throughout this process, the MDT members would communicate regularly in meetings or via shared documentation, allowing them to share updates on the patient’s progress, discuss any complications, and plan for discharge and ongoing care.

By working in collaboration, the professionals in the MDT can provide comprehensive, integrated care that addresses the patient’s needs on multiple levels, leading to a successful recovery from the broken hip.

Final Thoughts

To quickly summarise, by working together, multidisciplinary teams foster integrated care for patients, offering a streamlined approach that improves efficiency and reduces the risk of fragmented services.

As we’ve just seen, the collaboration of specialists from different domains provides a comprehensive framework for addressing complex cases, leading to better health outcomes for patients.

Despite initially being developed for cancer care services, the multidisciplinary team is now an integral component of modern healthcare and is one of the best ways we can deal with the most complex of patient cases.

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Article Contents

Part 1: multidisciplinary teams within geriatric medicine, part 2: high performing teams in healthcare, part 3: integrating evidence into practice.

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Understanding and improving multidisciplinary team working in geriatric medicine

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Graham Ellis, Nick Sevdalis, Understanding and improving multidisciplinary team working in geriatric medicine, Age and Ageing , Volume 48, Issue 4, July 2019, Pages 498–505, https://doi.org/10.1093/ageing/afz021

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Geriatric medicine is a speciality that has historically relied on team working to best serve patients. The nature of frailty in older people means that people present with numerous comorbidities, which in turn require a team-based approach to be managed, including allied health professionals, social work and nursing alongside medicine. The ‘engine room’ of the speciality has thus for many years been the multidisciplinary team (MDT) meeting—something other specialities have discovered only recently. Yet, rather paradoxically, the speciality has been slow compared to others (e.g. trauma, surgery, cancer) to reflect more formally on how team working can be enhanced, trained and supported in geriatric teams. This paper is a reflective review, grounded on our respective expertise in geriatric medicine and improvement science, on practice and its changing patterns within geriatric medicine, and the role of MDTs within it (Part 1). It offers a perspective from behavioural safety science, which has been studying team-working in healthcare for the last 20 years (Part 2) and concludes with practical suggestions, based on evidence, on how to integrate evidence and best practice into modern geriatric medicine-to address current and future challenges (Part 3).

Effective multidisciplinary teams (MDTs) and coordinated team meetings are core to successful comprehensive geriatric assessment.

Creating and enhancing high performing teams should be a priority in healthcare for older people.

Training together as MDTs can improve team performance and outcomes for patients.

Training in the speciality should prioritise non-technical skills (NTS) (leadership, communication, team-working, etc).

NTS and team-working should be regularly evaluated throughout clinical practice.

The gold standard of care for older people with frailty is comprehensive geriatric assessment (CGA) [ 1 ]. It has evolved over decades and across continents. The nature of frailty in older people means that people present with simultaneous problems across multiple domains [ 2 ]. That necessitates a multilateral approach and therefore a team who can address these separate domains simultaneously. Geriatric Medicine is not a technical specialty. It has no operating theatre, scope list, or procedures. The ‘engine room’ of the specialty therefore is the multidisciplinary team (MDT) it relies on for assessment and the meetings that facilitate coordinated care planning.

The aim of this paper is to offer a reflective review on MDTs and MDT meetings within geriatric medicine aiming to combine the clinical perspective with that of psychology and improvement science. The paper synthesises evidence from clinical geriatric research; and behavioural safety science—the authors’ respective areas of expertise. The synthesis is done in a reflective manner: we have jointly reflected on the implications of the latter for the former; and thought through existing clinical care and policy models in domains where MDT working is well-established and formalised, e.g. in cancer care. We have further situated our synthesis within current and predicted future patient population and associated clinical need expansion globally; as well as workplace (e.g. shiftworking patterns) and financial pressures.

In the past and perhaps typically but not uniquely in a British context, the MDT meeting might have been a once weekly sit down meeting on a geriatric ward with a consultant (attending) physician, senior nurse, physiotherapist and occupational therapist. These days, the MDT meeting is likely to take many forms depending on settings. Some are more suited to acute contexts, such as the acute admitting Geriatric wards. These are typically shorter and more focussed and usually delivered standing up—huddled around a ward white board. Other settings such as community hospitals or community meetings may involve larger teams meeting weekly to discuss more complex cases, perhaps including general practitioners, social workers and community rehabilitation teams.

Despite their differences in style and context, core elements of the geriatric MDT meeting are shared across teams (Box 1 [ 3 ]). These will classically include an assimilation of information across key domains such as medical, psychiatric and cognitive, social and functional [ 1 , 4 ]. They will include staff who understand their roles in the team meeting who will take responsibility for aspects of assessment or treatment [ 4 ]. Generally, there will be a goal established for a patient that might vary from simple treatment aims, such as mobilising independently, to complex discharge planning arrangements or longer-term functional outcomes. There should be agreed plans for short-term management to achieve these goals (such as dressing practice or cognitive assessments). These plans should be recorded and revisited to record progress, establish setbacks and revisit goals. Crucially, though there needs to be interaction with the patient and their family to establish a patient’s wishes and to feedback progress or manage expectations.

Establish patient centred goals.

Cover the domains of medical problems, functional ability, cognitive or psychiatric health and social circumstances.

Have representation from key disciplines.

Bring opinions together openly.

Agree an overall aim.

Agree next steps with time frames.

Allocate responsibility.

Reconvene to revisit progress regularly.

Communicate outputs from the MDT meeting.

The principles of effective MDT working cut across skills (e.g. good leadership), processes (e.g. good governance in documenting action plans) and critically values (e.g. centrality of the patient’s needs and respect for colleagues). The reason for this distinction is important is that it has implications for running MDT meetings as well as the training and resources required for MDTs to operate effectively. Behavioural evidence from cancer MDTs suggests that if one of the three elements is missing, then the MDT is likely to be ineffective or dysfunctional [ 5 – 7 ]—and in cancer care, this evidence has been translated into policy recommendations [ 8 ].

Evidence from CGA trialists

As part of the Cochrane Review of CGA [ 9 ], trialists were contacted and asked what elements of CGA they deemed to be essential through a structured questionnaire. The questionnaire included statements drawn from the existing literature of key elements of CGA to grade.

Thirteen trialists (of the 29 included) responded and ranked an MDT meeting as important to the CGA process. Other aspects highlighted as essential included plans tailored to the patient’s needs, specialty expertise and clinical leadership. Trialists were separately asked which team members and processes were present in both treatment and control arms of their RCTs. With the exception of Geriatricians, most staff including therapists and nurses were identical between treatment and control groups. MDT meetings, however, were only reported in 6 of the 13 control groups. This is suggestive that in addition to specialist knowledge and standardised assessments, having a coordinated team with clear meetings and a tailored plan for each patient is a critical difference between CGA settings and control groups in the available RCT evidence [ 1 , 9 ].

It is further suggested that there is a difference between CGA wards and mobile CGA team subgroups. The observed differences in the meta-analysis may represent subgroup underpowering, with fewer CGA team trials and trial participants. However, parallels exist between mobile stroke teams and stroke wards [ 10 , 11 ]. It is possible this pattern reflects the fact that discrete wards can foster more coordinated team working and the integration of assessment and care plans [ 1 , 9 ].

Terms such as multidisciplinary, interdisciplinary and transdisciplinary teams are often used interchangeably but are in fact conceptually different models of team-working as described in Box 2 [ 12 ]. These distinctions are not merely academic, but impact on how teams are set-up and work in practice and how they impact on patient care. In the CGA trials, often the control group included members of multiple disciplines—however, they reportedly worked independently of each other. The intervention groups however had a more integrated approach to the assessment of need, setting of goals and delivery of therapy. In clinical practice, teams may evolve into more integrated interdisciplinary and transdisciplinary working over time. Certainly, team cohesion and interconnectedness have been suggested in qualitative studies to correlate with a more effective team [ 13 ].

Multidisciplinary teams: The patient is assessed individually by several professionals (such as nursing, social work, psychiatry, medical, etc). Participants may have separate but inter-related roles and maintain their own disciplinary boundaries. The process might be described as additive, not integrative.

Interdisciplinary teams: Members come together as a whole to discuss their individual assessments and develop a joint service plan for the patient. Practitioners may blur some disciplinary boundaries but still maintain a discipline-specific base (for instance, aspects of functional assessment may be shared across disciplines). Teams integrate closer to complete a shared goal.

Transdisciplinary teams: Team members share roles as well as goals. This requires specialist practitioners to share their skills (allowing others to learn and take on skills) as well as acquire new skills in other areas from other practitioners. The result is a more blended team that shares objectives and many core skill sets required to achieve the overall goal.

These distinctions offer a framework to think about team-working and team development in practice. In some contexts, teams are able to develop new levels of close working when role blurring is introduced. This concept is best exemplified by an individual that is able to take on elements of someone else’s role in a setting to share the workload. For instance, an experienced nurse assessing for a walking aid in the ED, or a therapist discussing the meaning of a diagnostic test or discussing prognosis in a specialist clinic.

There are a number of descriptive models of teamwork—some are industry or speciality specific. The ‘Big Five’ model offers a comprehensive conceptual ‘umbrella model’, with reasonable empirical evidence, and offers a generalisable perspective on the constituent parts of effective team-working [ 14 ]. According to the model, effective team-working requires five core components; team leadership, team orientation, back-up behaviour (i.e. mutual support amongst team-members), mutual performance monitoring, and adaptability. These core elements are supported by three mechanisms that allow team-members to work well together: mutual trust, shared mental models (of the tasks to be performed and each other’s roles), and closed loop communication. We are not aware of a formal application of the Big Five model to geriatric medicine-to-date. The model offers good levels of face and content validity.

The above research helps articulate practical recommendations and approaches to ensuring high-quality team-working. For example, high performing teams are characterised by clear leadership with shared and regularly articulated vision [ 15 ] and are likely to be enabling, supportive and inclusive. Sharing values (such as a desire to achieve a quality of experience for patients) can unify a team [ 15 ]. Teams with shared values are able, for example, to highlight practices that do not fit with their ethos (e.g. unsafe practices).

Mutual respect for each other’s roles also fosters a cohesiveness to teams. If teams recognise what each member brings to the group, it encourages individuals to speak up and not be afraid of censure [ 16 ]. Creating a sense of psychological safety and an environment in which people share concerns is more likely to lead to the resolution of problems [ 17 ]. Being open to feedback can lead to opportunities to grow but requires a willingness to request and welcome feedback.

Technical and non-technical skills in healthcare

In the past two decades, healthcare has shown a keen interest in learning how to approach the training of effective teams and translating safety innovations from other high-risk industries. For instance, learning from the airline industry, healthcare recognised the role that breakdowns in communication and teamwork play in patient safety incidents. It adopted the use of incident reporting as a means to manage safety (i.e. with the aim to learn from incidents so the condition that triggered them are addressed). It has also introduced the distinction between technical and non-technical skills (NTS) [ 17 ].

The concept of NTS was introduced to differentiate them from the technical skill required to fly a plane. NTS were defined as ‘the cognitive, social and personal resource skills that complement technical skills and contribute to safe and efficient task performance’. Box 3 offers a distillation of the key NTS that have been recognised, assessed and trained in healthcare but also in other industries.

The distinction between different skills categories is useful as it allows development of assessment methods that are specific to each one of the skills. This offers a holistic assessment of competence—both in trainees (for example, in aviation [ 18 ]) and in experienced professionals, who have to revalidate regularly in order to maintain their licence to fly. An industry of simulators and simulation technologies has developed to train and assess pilots in a controllable and safe environment in which skills can be perfected and rare crises can be rehearsed without posing risks to passengers or aircraft.

Interventional specialties in healthcare followed suit, with simulators developed for complex invasive procedures (e.g. laparoscopy [ 19 , 20 ]), and skills assessments developed and validated to capture technical skills (e.g. OSATS [ 21 ]). In the last decade, similar assessment for NTS have developed for surgeons [ 22 ], anaesthetists [ 23 ], theatre nurses [ 24 ], ward teams [ 25 ] and medical students [ 26 ]—amongst other specialties. Although the evidence base is patchy, these skills have been shown to correlate positively with technical skills—which means that clinicians with better procedural and psychomotor (where applicable) skills also have better communication, leadership and personal resource skills [ 27 ].

Teaching and evaluation of NTS have been applied in older people’s settings in wards and simulation centres [ 28 ]. Here, training in NTS was aimed at improving compassionate and dignified care by enhancing empathy and communication. Staff found training together across disciplines enhanced the learning experience and felt more able to raise concerns. They also felt that their interaction with patients was enhanced.

A recent study even found that including older people as part of simulations for trainees allowed them to contribute to care improvement and gave them a sense of purpose [ 29 ]. Other recent innovations include use of MDT simulation to teach medical students the principles of MDT-based care management and planning for complex older patients and improve empathic skills [ 30 , 31 ].

Team training in healthcare

Training in NTS and team-working is possible both for individuals and perhaps more importantly for teams. Many years ago, it was suggested that simulation-based training prior to trainees practicing on patients is an ‘ethical imperative’ [ 32 ]. To-date, the imperative is yet to materialise. The availability of team training curricula, modules, facilities and faculty is rather haphazard—a situation not peculiar to the UK. A challenge for modern healthcare is that the provision and evidencing of systematic training in team skills should be a requirement of training and appraisal, not an optional scenario [ 33 ]. For a multidisciplinary specialty, such as geriatric medicine the acquisition and maintenance of such skills should be integral to specialty professional development and should apply to both trainees and consultants. Reflection should enable geriatric MDT members to identify the optimal team-working model for them (see Box 2 ); and develop their team to achieve the model.

To assume that an MDT will simply ‘work’ once it has been formed goes against the face of the evidence, both from outside the healthcare industry [ 34 ] but also within healthcare. Current healthcare training is ordinarily conducted in professional and specialty groups. It should not be surprising then that doctors and nurses who train in this individualistic manner cannot ‘automatically’ perform well as a team when brought together. Even in a specialist setting, the assembly of a team of experts does not necessarily make an ‘expert team’. Training as a team enhances team performance and clinical outcomes. The largest and most conclusive study to date was a large cohort study on perioperative care. Evaluating surgical team training across 108 Veterans Affairs Hospitals in the USA, staff reported improved aspects of team process including improved communication (42%) and improved teamwork (65%). More significantly, they saw an overall 18% reduction in postoperative mortality in the intervention sites compared with 7% respective in the control hospitals. Using propensity score matching to adjust for case-mix, the mortality difference was as high as a 50%. There was also a clear dose–response relationship between the level of training and mortality outcome with a reduction of one death per 2000 cases every quarter of additional training [ 35 ].

In this study, the training was of high intensity, including use of team skills and checklists. Whole teams attended training and subsequent coaching together. Training delivered to disciplines together can be associated with improvements in aspects of team process such as adherence to guidelines as well as in patient related outcomes [ 36 ], but importantly may be better than uni-disciplinary education when looking at aspects of personal efficacy in leadership and team-working [ 37 ].

MDTs will often have professionals with a range of experience and seniority. They may also change with the turnover of junior members of the team. Changes in junior doctors’ working patterns, a situation not unique to the UK but also present in Europe (e.g. through the European Working Time Directive) and the USA residents’ working hours, amongst other factors create a more transitional workforce often working in shifts. At the same time, this provides an opportunity for more multidisciplinary roles to emerge and complement the team. Working in these contexts with practitioners across different disciplines to achieve a positive outcome for a patient requires presence of good team skills and processes. MDTs meetings offer an opportunity to explore cases for learning points, and feedback from adverse events or even offer informal emotional support.

Geriatric medicine is the single biggest bed holding speciality in the UK and in many countries. Even where this is not the case, it remains a high resource specialty. Care for older hospital patients continues to rely heavily on good team-working, effective team leadership and smooth team communication to achieve coordinated care. Reviewing the training curricula for Geriatric Medicine from the UK, European Union, Ireland and the USA, whilst all endorse a knowledge of multidisciplinary working, only the US curriculum specifically encourages team training and evaluation [ 38 – 41 ]. It seems ironic then that the specialty that for so long has relied on its team based working to deliver high-quality patient care does not universally have a framework for joint training and evaluation in team-working. We view this as a challenge that the profession should rise to—such that both individual trainees are encouraged to develop their NTS; but also geriatric care teams start to train together.

In Box 4 , we have outlined strategies based on available evidence across healthcare specialities that geriatric medicine could consider adopting for both training but also care delivery.

Note: Core evidence supporting the proposed strategies can be found here for the skills, [ 8 , 14 , 15 , 17 , 28 , 29 , 34 , 42 ] processes, [ 8 , 43 , 44 ] and values [ 14 , 45 – 50 ] mentioned in the box.

Furthermore, from the perspective of acute care quality, it would also be logical that evaluation of team working in acute settings should feature in quality of care inspections or improvement plans. The processes of care, both technical and non-technical, and how these are promoted and supported (e.g. through regular training provision for which staff have allocated time) should be a focus of quality review and benchmarking.

The provision of high-quality care in acute hospital settings increasingly requires us to address variation in healthcare outcomes. To achieve that reduction in variation and deliver consistent high-quality experience, we need to explore methods of standardising high frequency elements of care to reduce harm. In surgical and anaesthetic settings, this is supported by using safety checklists. It may be that structured ward rounds and multidisciplinary meetings will need to have a more standardised approach to reduce the risks of a poor outcome.

Finally, the current and projected population trends (patients presenting with frailty and co-morbid conditions [ 51 ]) mean that the specialty needs to diversify to meet new demands throughout the hospital setting. This will inevitably mean drawing in new roles and new practitioners such as nurse and therapy consultants to be able to meet the demands. The specialty thus needs to develop a cadre of future consultants who are able to work with a broader MDT perhaps with more transdisciplinary working to support care delivery to a multimorbid patient cohort. One such example involves geriatric input into cancer MDTs [ 52 , 53 ], where significant value is added to patient care, as these patients do not just need cancer care but a more holistic approach. Another example involves geriatric input into complex and frail surgical patients. The Proactive care for Older People undergoing Surgery model offers a system of referral to the geriatric team and optimisation of these patients before and after surgical interventions [ 54 – 56 ]. Studies, including RCTs, over the last decade have shown a significant reduction in length of stay for such patients undergoing orthopaedic, urological and vascular surgery [ 57 ].

The reflective synthesis that we have offered here offers a novel perspective—to the best of our knowledge this is the first time that the clinical and behavioural evidence bases have been brought together. The strength of this synthesis is the breadth of evidence that we have covered, coupled with the respective expertise of the authors. These, however, are also its limitations: we did not attempt a systematic review of evidence—indeed one would not have been feasible across so many different literatures; and the evidence base within geriatric medicine requires further development. The perspective offered here rests on our interpretation of the evidence and personal experience of delivering and improving MDT-driven care. Subsequent research should put our recommendations to empirical evaluation.

Geriatric medicine will be in ever increasing demand. The speciality needs to fully embrace approaches to improve MDT working, such that we work optimally with colleagues and serve our patients.

Declaration of Conflict of interest: Sevdalis is the director of London Safety and Training Solutions Ltd, which undertakes patient safety and quality improvement advisory and training services for healthcare organisations internationally. Ellis has none.

Declaration of Sources of Funding: Sevdalis’ research is supported by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care South London at King’s College Hospital NHS Foundation Trust. NS is a member of King’s Improvement Science, which is part of the NIHR CLAHRC South London and comprises a specialist team of improvement scientists and senior researchers based at King’s College London. Its work is funded by King’s Health Partners (Guy’s and St Thomas’ NHS Foundation Trust, King’s College Hospital NHS Foundation Trust, King’s College London and South London and Maudsley NHS Foundation Trust), Guy’s and St Thomas’ Charity, the Maudsley Charity and the Health Foundation. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Ellis is a co-applicant on the NIHR grant (12/5003//01; ‘How to Implement Cost-Effective Comprehensive Geriatric Assessment’). None of the funders played any role in the writing of this article.

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Article contents

Interdisciplinarity: its meaning and consequences.

• Raymond C. Miller Raymond C. Miller Department of International Relations, San Francisco State University
• https://doi.org/10.1093/acrefore/9780190846626.013.92
• Published in print: 01 March 2010
• Published online: 20 November 2017
• This version: 27 August 2020
• Previous version

Interdisciplinarity is an analytically reflective study of the methodological, theoretical, and institutional implications of implementing interdisciplinary approaches to teaching and research. Interdisciplinary approaches in the social sciences began in the 1920s. At a minimum, they involve the application of insights and perspectives from more than one conventional discipline to the understanding of social phenomena. The formal concept of interdisciplinarity entered the literature in the early 1970s. The scholars responsible all shared the thought that the scientific enterprise had become less effective due to disciplinary fragmentation and that a countermovement for the unification of knowledge was the proper response. However, not all interdisciplinarians believe that the unification of existing knowledge is the answer.

There are many ways of differentiating between types of interdisciplinary approaches. One classification distinguishes between multidisciplinary, crossdisciplinary, and transdisciplinary approaches. Multidisciplinary approaches involve the simple act of juxtaposing parts of several conventional disciplines in an effort to get a broader understanding of some common theme or problem. Crossdisciplinary approaches involve real interaction across the conventional disciplines, though the extent of communication; thus, combination, synthesis, or integration of concepts and/or methods vary considerably. Transdisciplinary approaches, meanwhile, involve articulated conceptual frameworks that seek to transcend the more limited world views of the specialized conventional disciplines. Even though many believe that interdisciplinary efforts can create innovative knowledge, the power structure of the disciplinary academy resists interdisciplinary inroads on its authority and resources.

• academic discipline
• area studies
• interdisciplinary approaches
• interdisciplinarity
• interdiscipline
• multidisciplinary
• cross-disciplinary
• transdisciplinary

Updated in this version

Updated references; major revisions throughout.

Introduction

As early as the 1920s, the US Social Science Research Council (SSRC) recognized that, in only several decades after its invention, the departmental/disciplinary structure of the university was becoming an obstacle to effectively addressing comprehensive social problems. Especially in the 1930s, 1940s, and 1950s, the Rockefeller Foundation and then the Ford Foundation worked with the SSRC to fund interdisciplinary research and teaching in US higher education. In the early Cold War era, area studies programs were major recipients of that funding. As a consequence, international studies during this period were often conceptualized as interdisciplinary (Calhoun, 2017 ). At the founding of the International Studies Association (ISA) in 1959 , its mission statement explicitly states that the ISA “promotes interdisciplinary approaches to problems that cannot fruitfully be examined from the confines of a single discipline” ( International Studies Perspectives , May, 2007 , back cover).

The first section of this essay is a historical survey of selected professional literature on interdisciplinary studies, beginning with the classic 1972 OECD Report on its Paris conference (Apostel, 1972 ). It was the first major book entitled Interdisciplinarity . To achieve some conceptual clarity on the many varieties of interdisciplinary activity in the academy, basic terms were defined and a typology proposed. The second major part of this essay is structured by that typology of multidisciplinary, crossdisciplinary, and transdisciplinary approaches. Since all of these categories rely on disciplines as the core ingredient, discipline is also defined.

In recent years, the concept interdisciplinarity has become popular among scholars. Many books and articles have it in their titles. Books on interdisciplinary approaches vary from those promoting interdisciplinarity (Farrell, Lusatia, & Vanden Hove, 2013 ) to those denigrating it and praising the superior qualities of the disciplines (Jacobs, 2014 ). Furthermore, the widespread discussion of interdisciplinarity does not mean that it has politically succeeded in the academy. By and large the conventional disciplines have maintained their power over the university and funding bureaucracies. The last section of this essay discusses the varying fortunes of interdisciplinary approaches in the academy, especially in reference to international relations.

Historical Survey of Select Literature

The noun interdisciplinarity made its professional debut in a 1972 publication from the Organization for Economic Cooperation and Development (OECD). The report, entitled Interdisciplinarity: Problems of Teaching and Research in Universities (Apostel, 1972 ), was sponsored by OECD’s Parisian-based Centre for Educational Research and Innovation. The Report had chapters written by scholars from six different European countries: Austria, Belgium, France, Germany, Switzerland, and the United Kingdom. Though there were many differences between them, they all shared the thought that the scientific enterprise had become less effective due to disciplinary fragmentation, and that a counter movement for the unification of knowledge was the proper response. The problem was “how to unify knowledge and what the many implications of such unity are for teaching and research in the universities …” (Apostel, 1972 , p. 11). Unification “means the integration of concepts and methods in these disciplines” (pp. 11–12). A number of unifying schemas were proposed, including mathematics, linguistic structuralism, Marxism and general systems. Although the authors had different “transdisciplinary” proposals, they all agreed that “interdisciplinarity is a way of life. It is basically a mental outlook which combines curiosity with open mindedness and a spirit of adventure and discovery. . . .” It is practiced collectively. . . . It teaches that there can be no discontinuity between education and research” (Apostel, p. 285).

In addition to a number of important theoretical articles, the OECD report had a major emphasis on the design and implementation of interdisciplinary universities. The authors of that section, Asa Briggs of Sussex University and Guy Michaud of the University of Paris, gave as their sample model an interdisciplinary university with a special emphasis on international relations. They believed that because the field of international relations had the most complex connections, it necessarily involved the study of many methods, disciplines, issues, languages, and geographical areas. All students of their proposed university were expected to be familiar with the basic approaches and concepts of anthropology, politics, economics, international law, ecology, geography, history, sociology, and ethno-psychology (Apostel, 1972 , pp. 253–257).

Chronologically, the next major book that addressed the general issue of interdisciplinarity in the university setting was entitled Interdisciplinarity and Higher Education . It was published in 1979 , and its editor was Joseph Kockelmans, the Director of the Interdisciplinary Humanities Program at Pennsylvania State University. Possibly because he was European-educated, his orientation was similar to the authors of the OECD Report. He argued that only through “philosophical reflection” can the society’s intellectuals approach the “totality of meaning.” To overcome the fragmented worlds that they have created, they need to reach agreement not only on the position of the sciences, but also on “religion, morality, the arts and our sociopolitical praxis” (Kockelmans, 1979 , pp. 153–158). However, Kockelmans was opposed to using a pre-existing framework, such as the ones listed above in the OECD Report, or the logical positivism of the Unification of Science movement spearheaded by the Vienna Circle in the 1930s. None of them fulfilled the comprehensive vision that Kockelmans advocated.

In October of 1984 , OECD, in collaboration with the Swedish National Board of Universities and Colleges, decided to hold a conference to revisit the concept and experience of interdisciplinarity. More than half of the participants were from Sweden, and almost half of them were from one university, Linköping. Linköping University was especially interested in the topic because it had instituted a doctoral program based on four interdisciplinary themes (technology and social change, water in environment and society, health and society, and communication). The proceedings of the conference were published under the title Interdisciplinarity Revisited: Re-Assessing the Concept in the Light of Institutional Experience (Levin & Lind, 1985 ). Essentially the conferees agreed that the early enthusiasm for an interdisciplinary revolution was dampened by the realities of societal and institutional politics. Interdisciplinary research and teaching were still happening, but they were easier to accomplish if the participants did not boldly label them as such. The advisability of keeping a low profile was due to the fact that the “magical slot” from the mid 1960s to the early 1970s, in which interdisciplinary innovation had flourished, was replaced by a more conservative period in which disciplines reasserted their authority. George Papadopoulos of the OECD concluded that, “interdisciplinarity, even when it succeeds in unscrambling existing curricula, remains a hostage to the disciplines” (Levin & Lind, 1985 , p. 208).

The first major work on interdisciplinarity by an American-educated scholar was published in 1990 by Julie Thompson Klein, professor of humanities at Wayne State University. Her book is entitled Interdisciplinarity: History, Theory and Practice . Rather than making an argument for a particular approach, Klein provided a compilation of all the existing literature across all fields of knowledge. She concluded her extensive survey by observing:

Interdisciplinarity has been variously defined in this century: as a methodology, a concept, a process, a way of thinking, a philosophy, and a reflexive ideology. It has been linked with attempts to expose the dangers of fragmentation, to reestablish old connections, to explore emerging relationships, and to create new subjects adequate to handle our practical and conceptual needs. Cutting across all these theories is one recurring idea. Interdisciplinarity is a means of solving problems and answering questions that cannot be satisfactorily addressed using single methods or approaches. Whether the context is a short-range instrumentality or a long-range reconceptualization of epistemology, the concept represents an important attempt to define and establish common ground. (Klein, 1990 , p. 196)

Nowhere in Julie Klein’s extensive bibliography (97 pages long) is there mention of the term international relations or international studies , although she does have a section on area studies.

In 1997 , the Academia Europaea and the European Commission organized a conference in Cambridge, England around the topic “Interdisciplinarity and the Organisation of Knowledge in Europe.” The conference proceedings were published in 1999 under the same title (Cunningham, ed.). There were 24 contributors from 11 countries with most (9) coming from the United Kingdom. Several contributors referred back to the seminal article by Erich Jantsch in the 1972 OECD pioneering publication. Collectively they agreed that modern disciplines were a product of the scientific revolution of the 19th century . The specialized research entities of the University of Berlin seem to have been the origin of the disciplinary structure of knowledge. “Focusing scholarly attention on the essence or nucleus of the individual subject led inevitably to the putting-up of barriers” (Rüegg, 1999 , pp. 34–35). The division into insular, specialized disciplines was seen by sociologists as an almost inevitable outcome of the differentiation associated with the process of industrialization. John Ziman argued that the impetus toward greater and greater specialization had to do with the scholarly requirement for originality. It’s easier to be a “big frog in a small pond” (Ziman, 1999 , pp. 74–75). He concluded his essay by contending that “disciplines stand for stability and uniformity,” whereas “interdisciplinarity is a code word for diversity and adaptability” (pp. 81–82).

In the United States, some of the young scholars in international relations observed the disciplinary narrowing of the field and decided to publish a book in 2000 entitled Beyond Boundaries: Disciplines, Paradigms, and Theoretical Integration in International Studies (Sil & Doherty, 2000 ). A review (Miller, 2001 ) appearing in the newsletter of the Association for Interdisciplinary Studies observed that the book does not deliver on its promise to meaningfully discuss disciplines, paradigms, and theoretical integration; however, it does juxtapose different theoretical positions while calling for international relations scholars to be tolerant and willing to cross boundaries between disciplines and schools of thought.

In 2002 , an English academic, Joe Moran, published a book that he simply entitled Interdisciplinarity . Though broad in comprehension, it focuses on English and cultural studies. He argued that the institutional implications of openly pursuing interdisciplinary approaches are inevitably political, both in the hierarchy of knowledge and in the allocation of material resources (Moran, 2002 ). Oxford University Press decided to enter this academic realm by publishing the Oxford Handbook of Interdisciplinarity (Froderman, Klein, & Mitcham, 2010 ). None of the 37 chapters are primarily on international studies, though one of the chapters uses area studies as an example (Calhoun & Rhoten, 2010 ). In 2017 , the Handbook came out in a second edition (Froderman). Its 46 chapters address many issues, ranging from funding to pedagogy. However, there is still no chapter dedicated to international studies. The philosopher and editor Robert Froderman argued that “interdisciplinarity is the bridge between academic sophists (disciplinarians) and the rest of society” (p. 7).

In 2009 , Pami Aalto of Tampere University in Finland embarked on a major project to discuss and showcase interdisciplinary approaches in international studies. Two books emerged from the project. The first was International Studies: Interdisciplinary Approaches (Aalto, Harle & Moisio, 2011 ), and the second, Global and Regional Problems: Towards an Interdisciplinary Study (Aalto, Harle, & Moisio, 2012 ). Aalto and his fellow editors argue, “We want to assert that International Studies—as a wider field of studies than International Relations—must necessarily be more interdisciplinary than International Relations ever was during its golden era from the 1950s onwards” (Aalto et al., 2011 , p. 3). They observed that, in the inter-war period, international studies was an interdisciplinary field with materials and perspectives drawn from many fields and disciplines. They noted that this sense of the field was spelled out in the 1939 League of Nations publication University Teaching of International Relations (Zimmern) as well as Quincy Wright’s magnum opus The Study of International Relations ( 1955 ). Despite Wright’s extraordinary effort to synthesize over 20 fields into the study of international relations, his influence over the subsequent development of the field has been minimal. International relations, especially in the United States from the 1950s on, has become more and more embedded in political science. A key reason for this evolution was the focus on the cold war power conflict. Ironically, a major intellectual force in this development was Quincy Wright’s colleague at the University of Chicago, Hans Morgenthau. However, with the end of the Cold War era, Aalto and his fellow editors were hoping for the emergence of a broader, more diverse, interdisciplinary approach to international studies (Aalto et al., 2011 , pp. 11–19).

In 2013 , two European-based scholars, Andrew Barry and Georgina Born, published a book in which they claimed to rethink what is meant by interdisciplinarity, entitled Interdisciplinarity: Reconfigurations of the Social and Natural Sciences . For instance, the authors challenge the conventional statement that interdisciplinary activity is about combining and integrating knowledge from existing disciplines. They believe that interdisciplinarity is about gathering knowledge from all available sources, not just disciplines. They point to community-based knowledge, local experience, and indigenous knowledge, among other sources. Also, they start with the premise that neither disciplinary nor interdisciplinary activities are monolithic or unchanging. Disciplines do have the political advantage in the academy because they usually control the curriculum and the budgets that include faculty hiring. Thus, the disciplines have considerable control over the conditions that determine the degree of receptivity to interdisciplinary research and teaching in any particular university setting. In Barry and Born’s opinion, truly interdisciplinary activities have qualities that differentiate them positively from the disciplines. These three qualities are accountability, innovation, and ontology. Accountability means being more responsive to societal needs. Innovation means being more practical about the problems that are addressed. And ontology means that interdisciplinary activities are more likely to be relational, holistic, and to view humans as being embedded in nature. Also, they respect the participation of the public in the discovery and application of knowledge. But interdisciplinary programs come and go. Some have staying power and become established interdisciplines, even new disciplines. Some get absorbed, whereas others disappear altogether. “The chapters in this book attest to the heterogeneity that characterises both disciplines and interdisciplines and the necessity of probing the genealogies of particular interdisciplinary problematics” (Barry & Born, 2013 , p. 41).

The American Political Science Association noted the increasing popularity of interdisciplinary rhetoric and practice, and in 2007 , they established a Task Force to study it. The report of the Task Force was published under the title Interdisciplinarity: Its Role in a Discipline-Based Academy (Aldrich, 2014 ). The report is interesting because of the obvious tension that permeates the document between proponents of disciplinarity and interdisciplinarity. The first chapter reiterates the value of disciplines. The Task Force Chair, John Aldrich, argued that disciplines are the foundation of knowledge and the academy. In his view, interdisciplinary efforts often lack valid and reliable measures for judging scholarship and teaching, and thus are inherently inferior. Nevertheless, in a subsequent chapter, four pioneers of interdisciplinary scholarship argued for the superior merits of interdisciplinary approaches. The four are David Easton (systems), R. Duncan Luce (cognitive science), and Susanne and Lloyd Rudolph (area studies). In fact, Easton stated, “I don’t see anything that can possibly be exciting and not be interdisciplinary. I think the disciplines have sort of exhausted their contributions to our understanding of politics” (Aldrich, 2014 , p. 55). Lloyd Rudolph concluded his interview by offering this reflection: “I realize that it is not only that I value interdisciplinarity but also that I value being allowed to think out of the box of disciplinary methods. New concepts reveal new realities” (Aldrich, 2014 , p. 72).

In 2013 and 2015 , two books were published that had both “interdisciplinary” and “international relations” in their titles. The first was Interdisciplinary Perspectives on International Law and International Relations: The State of the Art , edited by Jeffrey Dunoff and Mark Pollack ( 2013 ). A more accurate title would have been “interdisciplinary perspectives on the historical relationship between international law and international relations.” The authors noted that during the inter-war period, scholars in the two fields worked very closely together. However, with the advent of World War II and the rise of realism as the dominant theory in international relations, the study of law was considered irrelevant, as unenforceable international law does not affect the behavior of nation-states. Furthermore, normative law was considered too non-scientific for the post-World War II behavioralists/positivists political scientists. It’s worth noting that the editors consider international relations a discipline and that they seem to use it interchangeably with political science. With the rise of other theories in international relations that challenged the dominance of realism, international law became a more acceptable ingredient of international relations scholarship in the 1990s and thereafter. However, instead of a more equal relationship between two disciplines, international law was often considered a subject rather than a discipline. Or as the editors put it, “the intellectual terms of trade were asymmetrical” (Dunoff & Pollack, 2013 , p. 649). The interdisciplinary perspective of the editors and their fellow authors is reflected in their call for more pragmatic, eclectic theoretical approaches drawn from both international relations and international law. “Our call therefore is not for token inclusion of international law approaches, but rather for an interdisciplinary version of the pragmatic, analytically eclectic, tool-kit approach” (p. 653).

The second book, edited by Patrick James and Steve Yetiv, was Advancing Interdisciplinary Approaches to International Relations (Yetiv & James, 2015 ). Their advancement illustration is the application of many perspectives from different disciplines and interdisciplines to the topic of conflict studies. These include history, political science, psychology, neuroscience, anthropology, gender studies, technology studies, demography, and systems analysis (p. 324).

In 2016 , the British Academy published a report on its investigation of interdisciplinary research and teaching in higher education in the United Kingdom. It is entitled Crossing Paths: Interdisciplinary Institutions, Careers, Education and Applications . The working group was chaired by David Soskice of the London School of Economics. In his preface, he recognized the need to promote interdisciplinarity. According to him, this was necessary because the universities, the research councils, the journals and publishers were organized along disciplinary lines. “The incentive structures set up by the interplay of these institutions militates against interdisciplinarity” (p. 5). Then, paradoxically, Soskice went on to argue, as did the group report, that the best way to promote interdisciplinarity is the support of “strong disciplines” (Soskice, 2016 , p. 6). This seems like a strategy that would perpetuate the problem they have identified. The group recommended that junior faculty should first make their reputations in a home discipline. Only then would it be safe to venture into interdisciplinary territory (p. 9). However, once socialized in the discipline’s world view, it’s less likely that faculty will venture into interdisciplinary territory.

The British Academy report recognizes that getting a credible and fair evaluation of interdisciplinary research is very difficult in a discipline-controlled environment. Nevertheless, the working group recommended “evaluating the whole and not just disciplinary parts of any interdisciplinary output. The quality of interdisciplinary work lies in the way that it brings disciplines together” (Soskice, 2016 , p. 10). The evaluation chapter provides a set of guidance questions for research-review panels for evaluating interdisciplinary research proposals. One of the questions asks whether the proposal shows “an understanding of the challenges of interdisciplinary integration, including methodological integration, and the human side of fostering interactions and communication.” Therefore, it is not surprising that the chapter ends with the statement, “a focus on interdisciplinarity revives a sense of the academy as a holistic intellectual and social organism, integrated into the wider community, in which multiple flows and exchanges between all of its parts ensure its vitality” (Soskice, 2016 , p. 70).

In 2019 , Issues in Interdisciplinary Studies dedicated an entire issue to the work of the most prolific American scholar of interdisciplinarity, Julie Thompson-Klein (Augsburg, 2019 ). Her newest book is scheduled to be published in 2021 with the title Beyond Interdisciplinarity: Boundary Work, Communication, and Collaboration in the 21st Century . The book focuses on a full range of sector-crossing, including not only academic disciplines, but also occupational professions, interdisciplinary fields, public and private spheres, local communities, project stakeholders, and countries and cultures across the globe, wherever knowledge production is occurring. This new book is an update and extension of her earlier work, Crossing Boundaries: Knowledge, Disciplinarities, and Interdisciplinarities (1996) .

Academic Discipline

Disciplines are the basic units in the structure of knowledge that have been “historically delineated by departmentalization. Within each discipline there are rational, accidental, and arbitrary factors responsible for the peculiar combination of subject matter, techniques of investigation, orienting thought models, principles of analysis, methods of explanation and aesthetic standards” (Miller, 1982 , p. 4). They constitute the bureaucratic subcultures of the modern university. The modern disciplinary system was established at the turn of the 19th into the 20th century .

Many scholars have tried their hand at the task of explicating the characteristics of an academic discipline, but the list provided by Arthur King and John Brownell ( 1966 ) in The Curriculum and the Disciplines of Knowledge still seems among the clearest and most comprehensive. Below is this author’s version of their original list:

Field of demarcated study (subject matter boundaries, inclusions and exclusions).

Shared set of underlying premises (basic assumptions about how the world works).

Shared set of concepts (jargon).

Shared set of organizing theories/models (explanatory frameworks).

Shared set of truth-determining methods (what counts as data—how to make sense of them—i.e. research protocols).

Shared set of values and norms (preferred approaches to the material field that is studied by the discipline—e.g. economists prefer the approach of the free market; also preferred conduct by the practitioners of the discipline).

These six qualities cumulatively come together as a unique perspective—a coherent world view—a disciplinary paradigm or matrix.

Community of scholars who share this world view (professional identity—academic tribes ).

Shared set of literature and great scholars in the discipline.

Agreement on what to teach (structure and content of the basic texts and curriculum from the introductory course to the advanced graduate seminars).

Means of reinforcing the professional standards (graduate training, hiring and tenure control, associations, conferences, peer-reviewed journals, and grant-making processes).

Departmental home in a college/university (bureaucratic recognition, resource allocation and territorial ownership).

Ideal-type conceptualizations of this nature have great heuristic value, but applying them in the “real world” becomes problematic. After all, every group of faculty organized around a defined academic interest that has aspirations for permanence, wish to be known, at least eventually, as a discipline. Recognition as a discipline means more prestige and the prospect of more dependable institutional support. A working solution to this definitional problem is to limit the designation of discipline to those departmental groupings that appeared at the beginning of the 20th century and have institutionally solidified their presence in the academy over the past 100 plus years. John Ziman called them the “Grand Old Disciplines” ( 1999 , p. 73). Thus, in the social sciences, the conventional and building-block disciplines would be Anthropology, Economics, Geography, History, Political Science, Psychology and Sociology. Without some kind of limitation on the use of the designation discipline, even the distinction between discipline and interdisciplinary can become meaningless. Nevertheless, the solution proposed is admittedly an arbitrary one, but the historical process that created these disciplinary conglomerates in the first place was also a relatively arbitrary process. Eric Wolf argued that the field of classical political economy was divided into the specialized disciplines of economics, political science, sociology and anthropology in a process that lost touch with the real world.

Ostensibly engaged in the study of human behavior, the various disciplines parcel out the subject among themselves. Each then proceeds to set up a model, seemingly a means to explain “hard,” observable facts, yet actually an ideologically loaded scheme geared to a narrow definition of subject matter. (Wolf, 1982 , p. 10)

The establishment of these specialized disciplines at the beginning of the 20th century has been called the “academic enclosure” process (Becher, 1989 ). In a few decades, these disciplines had enclosed themselves in departmental organizations that gave them long-term bureaucratic protection. Yet these disciplines, according to Weingart and Stehr, are “the eyes through which modern society sees and forms its images about the world, frames its experience, and learns, thus shaping its own future or reconstituting the past” (Weingart & Stehr, 1999 , p. xi). Stephen Turner argued that “disciplines are shotgun marriages . . . and are kept together by the reality of the market and the value of the protection of the market that has been created by employment requirements and expectations (Turner, 1999 , p. 55). Turner believed that the disciplines’ animosity toward interdisciplinary initiatives was primarily driven by protectionism (p. 50).

The seventh disciplinary characteristic notes that the first six qualities come together in a world view that is unique to each discipline. Comparing world view components is a useful method for both disciplinary and interdisciplinary scholars. The concept has German origins and has been productively utilized in many academic and non-academic venues for 150 years. This author was introduced into the way anthropologists use the world view method by Robert Redfield ( 1956 ). According to Redfield, every culture or sub-culture has a world view, its embedded “mental map.” It provides guidance on the nature of the world, how we know the truth about it, what is right and wrong behavior, and what emotionally matters the most. Cognitive linguist George Lakoff contended that “World views are complex neural circuits fixed in the brain. People can only understand what fits the neural circuitry in their brains. Real facts can be filtered out by world views” (Lakoff, 2017 ). Critical psychologist Michael Mascolo noted “the concept of world view is founded on the epistemological principle that observation of the physical and social world is a mediated rather than a direct process” (Mascolo, 2014 , p. 2086). He reaffirmed Redfield’s point that a complete world view has an ontology, an epistemology, and a normative belief system.

Table 1. Post-World War II Macro Social Sciences: Comparative Attributes

Source : Miller, R. C. ( 2018 ). International political economy: Contrasting world views (2nd ed., p. 17). London, UK: Routledge.

This author has used world view as the comparative method in understanding the different schools of thought in international political economy (Miller, 2018 ). One step in this process was identifying the comparative attributes of the basic contributing disciplines. A summary of that analysis is in Table 1 : Post World War II Macro Social Sciences: Comparative Attributes. Economics, political science, and sociology are compared in six fundamental dimensions: core subject matter, central concepts, explanatory strategies, normative orientation, data collection, and data analysis.

Interdisciplinary Approaches

Interdisciplinary approaches in the social sciences involve, at a minimum, the application of insights and perspectives from more than one conventional discipline to the understanding of social phenomena. Interdisciplinarity , on the other hand, is an analytically reflective study of the methodological, theoretical, and institutional implications of implementing interdisciplinary approaches to teaching and research. Strictly speaking, interdisciplinarians are those who engage in the scholarly field of interdisciplinarity, though there are many faculty and others who participate effectively in interdisciplinary projects without being reflexive about its methods, theories, and institutional arrangements. On the other hand, interdisciplinary participants are more likely to be aware of their underlying world views than disciplinarians.

There are many ways of differentiating between types of interdisciplinary approaches, and in fact, of defining the basic term, interdisciplinary. For instance, the National Academies of Science propose that:

“Interdisciplinary research is a mode of research by teams or individuals that integrates information, data, techniques, tools, perspectives, concepts, and/or theories from two or more disciplines or bodies of specialized knowledge to advance fundamental understanding or to solve problems whose solutions are beyond the scope of a single discipline or area of research practice.” (National Academy of Sciences, 2005 , p. 39)

This definition privileges the process of “integration” as well as identifying “disciplines” as the primary source of the ingredients to be integrated. Lisa Lattuca, in her faculty-interview study Creating Interdisciplinarity ( 2001 ) argued that post-structuralists, like herself and all the humanities professors and most of the social science professors in her study, reject both of these privileging assumptions. They argue that integration presumes harmonious order, whereas reality may be full of oppositions and contradictions, and that using disciplines as the basic raw material legitimizes their monopoly over knowledge. However, all of the natural scientists in her study were comfortable with the type of definition proposed by the National Academies (Lattuca, 2001 , p. 104). The Political Science Task Force Report also accepted it. Nevertheless, interdisciplinary approaches could be broadened to include the processes of juxtaposition, application, synthesis, and transcendence as well as integration.

By utilizing this broader definition of interdisciplinary approaches that includes processes other than integration, the logic of the original OECD typology retains its efficacy. That typology divided interdisciplinary approaches into multidisciplinary, crossdisciplinary, and transdisciplinary. What follows is this author’s version of that typology.

Multidisciplinary Approaches

Multidisciplinary approaches involve the simple act of juxtaposing parts of several conventional disciplines in an effort to get a broader understanding of some common theme or problem. No systematic effort is made to combine or integrate across these disciplines. This is the weakest interdisciplinary approach, and it actually enhances the stature of the participating disciplines because their identities and practices are not threatened. They do not need to change any of their protocols, yet they can claim their openness to interdisciplinary cooperation. Cafeteria-style curricula, team-taught courses, ad hoc research teams, and conference panels could be examples of this approach.

Crossdisciplinary Approaches

Crossdisciplinary approaches involve real interaction across the conventional disciplines, though the extent of communication and thus combination, synthesis or integration of concepts and/or methods varies considerably. Since the variety of crossdisciplinary approaches is so great, this author has created a further six-fold typology. The six sub-categories of crossdisciplinary approaches are: (a) topics of social interest, (b) professional preparation, (c) shared analytical methods, (d) shared concepts, (e) hybrids, and (f) shared life experiences (Miller, 1982 ). Hundreds of crossdisciplinary combinations have been created over the course of the last 100 years. Some of these combinations have been ephemeral, some long lasting, but poorly articulated, and some have developed an institutionalized coherence that rivals the conventional disciplines. The latter in this author’s taxonomy are the interdisciplines . David Long, one of the authors in Aalto’s first book called them “neodisciplines” (Long, 2011 , pp. 52–59).

Transdisciplinary Approaches

Transdisciplinary approaches, according to Jantsch’s classic essay ( 1972 ), involve articulated conceptual frameworks that seek to transcend the more limited world views of the specialized disciplines. These frameworks are holistic in intent. In the 1972 OECD volume, the transdisciplinary approaches mentioned were general systems, structuralism, Marxism, and mathematics. The 21st century transdisciplinary movement in Europe believes that the broader public should be involved in providing, testing, evaluating, and implementing knowledge across all fields. Academic disciplines, therefore, are only a part of the picture.

Social Topics

Important social topics frequently attract members from several disciplines. They start out as multidisciplinary groupings, but over time continuous communication creates a new crossdisciplinary field of study. Examples would include environmental studies, cognitive science, gerontology, labor studies, peace studies, and urban studies. The study of geographical regions, area studies, is an interesting topical example because of its close relationship to international relations.

Professional Preparation

Another organizing principle for crossdisciplinary combinations is relevant knowledge for professional preparation . Examples include business management, diplomatic studies, education, public administration, health services, and policy studies. There are undoubtedly more students, faculty, and practitioners in this professional category than in any of the other categories, but the self-conscious attention to their interdisciplinary nature is very limited. Nevertheless, there are exceptions; for instance, Donald Schön ( 1983 ) in his book The Reflective Practitioner observed that the professions are split between the rational technocratic view of the more theoretical and conventional perspective vs. the more particularistic uncertainty of the actual field situations. He tried to find a middle ground between these extremes by proposing a reflexive approach that combines theory and practice. He argued that professionals should be aware of the frames within which they operate so that they are open to critiquing the one they are using and even shift to another if the situation requires it. Schon’s proposed approach is similar to the interdisciplinary method of comparative world views or multi-perspective analysis (Miller, 1982 ).

Policy studies, a growing field in recent years, manifest this internal tension rather dramatically. In the early 1950s, Harold Lasswell expressed his belief that through a rational and scientific process the best policy options could be identified and implemented toward the betterment of democratic objectives. Some of the analytical methods he advocated, such as benefit/cost analysis, are still being applied today. However, his approach has been criticized as being undemocratic, that is, “scientists know better,” and incredibly unrealistic as the political decision-making process is anything but rational. Studying the “different perspectives that underlie conflict in public policy arenas . . . is more illuminating and ultimately more practical than quixotically tilting at scientific windmills” (Smith & Larimer, 2009 , p. 18).

Shared Analytical Methods

Similar research methods, especially the quantitative ones, are often shared across the disciplines. They provide a basis for bringing methods-oriented faculty members together in more permanent crossdisciplinary associations. These groups have conferences, journals, and even academic programs. Examples of these shared analytical methods include statistics, computer modeling, game theory, and information theory (Miller, 1982 ). However, despite the potential cost savings, conventional disciplinary departments are usually unwilling to replace their own methods courses with the more generic ones from these crossdisciplinary programs.

Shared Concepts

There are some major concepts that appear in many disciplines that have the potential for crossdisciplinary integration. Classic examples of shared concepts include energy, value, flows, role, evolution, development, and cycles (Abbey, 1976 ). George Homans, a sociologist in Harvard’s crossdisciplinary Social Relations Department in the 1960s and 70s used exchange as his main integrating concept. The source of his inspiration was rational exchange theory from the discipline of economics (today it would be called rational choice theory). He made an explicit effort to use benefit/cost exchange as the basis of a theory of human behavior that could integrate across disciplines. Homans argued that although the specifics of exchange relationships may vary across different types of human experience, their overall interactive form may be quite similar (Homans, 1974 ).

The concept of development was dominant in the social sciences in the 1950s and 1960s under the crossdisciplinary umbrella of modernization theory. Modernization theory grew out of the need to achieve some degree of coherent coordination between the different and sometimes contradictory development strategies proposed by the separate social science disciplines. Economists argued that development would occur if sufficient amounts of capital investment are made and markets are developed. Political scientists argued that development requires modern bureaucracies, effective governance, and political participation. Sociologists argued that modern social institutions such as factories, schools, and mass media are key components in any development plan. Anthropologists argued that the residents of poor countries had to change their traditional cultural values into modern ones if development were to occur. Psychologists argued that individual personality development is the key, shifting the orientation from ascription to achievement. Modernization theory tried to bring all of these diverse perspectives together. It was the central organizing theory of the crossdisciplinary field of development studies.

The most widely recognized type of crossdisciplinary approach is undoubtedly the hybrids . Hybrids combine parts of two existing, related disciplines to form interstitial new crossdisciplines that attempt to bridge perceived gaps between disciplines (Miller, 1982 ). Well-known examples include social psychology, political economy, biogeography, and historical sociology. Sometimes the hybrid crossdisciplinary fields generate new theories whose promise is so great that they are borrowed back into their constituent disciplines. Social psychology’s symbolic interaction theory is a case in point. In fact, Dogan and Pahre ( 1990 ) argue that hybrid activity is the most likely source of innovative advances.

One of the most important hybrids in the interdisciplinary realm of international relations is political economy, especially in the form of international political economy (IPE). IPE uses the multi-perspective approach mentioned above. It juxtaposes the competing explanatory perspectives of the market model from economics, institutionalism from political science and sociology, and historical materialism from classical Marxist political economy (Miller, 2018 ). The differing perspectives provide a rich treasury of insights, understandings, critiques, and research strategies.

Shared Life Experiences

The basic premise in crossdisciplinary programs based on shared life experiences is that certain groups have shared a common experience of oppression that gives them a shared identity, a shared rejection of mainstream knowledge that reinforces this oppression, and a shared political agenda to replace the unjust social conditions with an egalitarian society. Three major examples of this category are women’s studies, ethnic studies, and post-colonial studies. These crossdisciplinary fields entered the academy as outgrowths of the social movements of the late 1960s and early 1970s. They started out as multidisciplinary challengers to the disciplinary/departmental power structure of the university, yet over the past four decades women’s studies and ethnic studies have evolved increasingly into discipline-like programs, in other words, interdisciplines. According to some observers, one of the costs of this institutional acceptance was the loss of one of the early objectives of these movements, social change activism in the community (Messer-Davidow, 2002 ).

Virtually all of the over 700 women’s studies programs in the United States teach feminist theory, an integrating perspective that focuses on socially constructed gender systems and standpoint analysis. Standpoint theory contends that how one perceives any human condition depends on the position that one occupies in the society. Those who are being oppressed are going to see things very differently than those who are doing the oppressing.

According to Ann Tickner, feminism challenges the neo-positivist and state-centric orientation of international relations in the United States. The unequal relationships that pervade the world are socially constructed and vary from place to place, with women suffering universally from male-dominated exercises of power. Furthermore, dichotomies such as those that “separate the mind (rationality) from the body (nature) diminish the legitimacy of women as ‘knowers’” (Tickner, 2014 , p. 86). Knowledge should not be pursued for its own sake or for the benefit of the state but in order to facilitate the emancipation of the oppressed (Tickner, 2014 , pp. 176–77).

Theorists in African-American or Africana studies have made a deliberate effort to incorporate the perspective of women in their key concept, Afrocentricity . The meaning of Afrocentricity is somewhat contested within the interdiscipline, but there is no doubt about what it opposes, namely Eurocentrism. Among the specified features of Eurocentrism are reductionism, individualism, and domination over nature, whereas Afrocentricity is associated with holism, community, and harmony with nature (Azibo, 2001 , p. 424). Karanja Keita Carroll ( 2008 ) contended that the “Afrikan worldview” has embedded within it an African culture-specific axiology, epistemology, logic, cosmology, ontology, teleology, and ideology that necessitate a research methodology that is consistent with these components. Instead of the Eurocentric approach that emphasizes objective detachment, separation between the knower and the known, material reality as primary, either/or logic, and knowledge for knowledge’s sake, the Afrikan worldview emphasizes full engagement, the blending of knower and known, the spiritual essence of reality as primary, both/and logic, and knowledge for the betterment of African peoples. Africana research is about participation, relationships, interdependence, and the liberation of Africana people (Carroll, 2008 , pp. 4–27).

Advocates for transdisciplinary approaches often directly challenge the efficacy of conventional disciplines, claiming that they are part of the problem rather than the solution, especially when the objective is the mitigation of complex social problems. Proponents of transdisciplinary approaches frequently accuse the hegemonic conventional disciplines of protecting the status quo rather than promoting progressive change. The framers of some transdisciplinary approaches see them as providing alternatives to the world views of the conventional disciplines that they would replace. Examples of discipline-replacement transdisciplinary approaches would be general systems theory, Marxism, cultural studies and sustainability studies. Examples of transdisciplinary approaches that could supplement rather than replace conventional disciplines would be symbolic interactionism, rational choice theory, and gender theory (Miller, 1982 ).

General systems theory, the transdisciplinary approach that Jantsch favored, contends that nature is a hierarchy of similar structures up through the whole succession of physical, biological, and social systems. There are similar developmental patterns throughout nature, but there are different paths that can lead to the same destination. Through the organization of energy from the environment (negative entropy) and communication with the environment (negative feedback), systems seek to maintain dynamic equilibria. This theory conceives of nature as a holistic set of relationships that thrives on diversity.

David Easton introduced systems thinking to political science in the 1950s and 1960s because he felt the discipline was too narrow. “I am not a political scientist but rather a social scientist interested in political problems” (Aldrich, 2014 , pp. 52–53). Currently, Carolyn and Patrick James continue Easton’s systems approach with their application of “systemism” to foreign policy analysis. However, in their view, systemism moves away from Easton’s bias toward homeostatic proclivities and emphasis on the macro level. Systemism includes both the macro and the micro and all forms of interaction between them (James & James, 2015 ).

Since the 1960s, general systems theory has been the main transdisciplinary approach of environmental or ecological studies (Costanza, 1990 ). Today, this field is most likely to be called sustainability studies. In a major conference on transdisciplinarity held in Switzerland in 2000 , sustainability was put forward not only as the major reason for the necessity of transdisciplinarity, but also as a transdisciplinary approach in itself (Klein et al., 2001 ). However, Egon Becker argues that sustainability studies is a “transdisciplinary field” that is more of a “conceptual and heuristic framework” than a general theory ( 1999 , pp. 284–285).

The lack of an agreed-upon general theory for engaging in the intellectual process of integrating across disciplines led William Newell to search for the most comprehensive and functionally effective transdisciplinary theory. He decided on general systems. But the first difficulty that Newell faced was deciding on which version of general systems theory to embrace. He identified eight possibilities: chaos, complex systems, fractal geometry, nonlinear dynamics, second-order cybernetics, self-organizing criticality, neo-evolutionary biology, and quantum mechanics (Newell, 2001 ). After studying them all, he chose complex systems as the preferred approach. Newell ( 2001 , p. 7) explains: “Specifically, the theory of interdisciplinarity studies that I am advocating focuses on the form of complexity that is a feature of the structure as well as the behavior of a complex system, on complexity generated by nonlinear relationships among a large number of components, and on the influence of the components and relationships of the system on its overall pattern of behavior.” Newell presented his preferred theory to a panel of well-known interdisciplinarians for their reactions. None of the six respondents agreed with his suggestion, primarily because they did not believe that the range and diversity of interdisciplinary possibilities could be captured within one theoretical framework (Issues in Integrative Studies 19, 2001 , pp, 1–148)

One of the respondents to Newell’s proposal, Richard Carp ( 2001 ), took issue with his basic premise, namely that the knowledge to be integrated via complex systems theory comes exclusively from existing disciplines. Carp insisted on widening the knowledge sources. He stated that we should stop thinking of “the disciplines as unique sources or resources for knowledge and thought” (Carp, 2001 , p. 74). Carp argued that we should “learn from multiple knowledge formations” (p. 75). Disciplines should not be the “gatekeepers.” The universities are just one of the many institutions in society that not only possess knowledge but can also create it. We should not be talking about interdisciplinary studies but “knowledge formations” (p. 75).

In Europe, the transdisciplinary movement has taken several different directions. The Swiss Academies of Arts and Sciences conference in 2000 promoted a process form of transdisciplinarity that transcended not only disciplinary boundaries, but also the boundary between the scientific establishment on the one hand and the users of the results of scientific research on the other hand. Users include government agencies, businesses, non-profit organizations, and members of the general public. Since all of these groups are stakeholders in the solution of the societal problems that science has an obligation to address, they should all be present at the table in the research process. In fact, the more stakeholders involved, the more “robust” the research. “We take the contributions to the informing and the rationalizing of actions in their societal context to be the main performance of problem-oriented research, and by implication, also of transdisciplinary research” (Zierhofer & Burger, 2007 , p. 57). In other words, according to the Swiss school, the purpose of transdisciplinary research is to seek and facilitate the implementation of solutions for societal problems, such as violence, poverty, and global warming, that serve the common good (Pohl & Hadorn, 2008 ). Norwegian professor Willy Ostreng, in his major book on interdisciplinary research, agrees and adds that as transdisciplinarity traverses the boundaries between science and stakeholder expertise it creates a new science, a “post-normal” science (Ostreng, 2010 , pp. 29–33).

Another European school of transdisciplinarity is centered around Basarab Nicolescu, a French academic. His group is organized around the International Center for Transdisciplinary Research. The movement’s objective is the achievement of the totality of meaning across all the sciences, art, religion, and cultural perspectives. That endeavor involves the search for relations and isomorphisms across all realms. The French school’s epistemology is explicitly non-Aristotelian in that it wishes to go beyond lineal and binary logic. They recognize different levels of reality in which different modes of understanding prevail. They start with the differences between classical physics and quantum physics, between reason and intuition, between information and consciousness, and between linear and non-linear logics. Non-linear logic is explained as the unity of oppositions, the inclusion of the excluded middle, and the evolutionary process of ever more comprehensive syntheses. Manfred Max-Neef calls this epistemology “strong transdisciplinarity.” He sees some of it in the natural sciences, especially in quantum physics and complexity theories. However, he does not see any of it in the social sciences. He sees economics as the most retrogressive and therefore one of the biggest obstacles to a unified, spiritually evolved, sustainable future (Max-Neef, 2005 , pp. 5–16).

There are some interesting analogies between “strong transdisciplinarity” and the field of cultural studies, for which many claim transdisciplinary status. Both approaches are strongly critical of the excessive reliance on rationality and analytic reductionism, as well as of the fragmented specialization of the structure of knowledge. The location of cultural studies at the interface of the humanities and the social sciences enables its practitioners to bring together their different concepts of culture and then to add the additional dimension of everyday meanings and practices present among the broader population (Moran, 2002 ).

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Peer-reviewed

Research Article

Determinants of post-acute COVID-19 syndrome among hospitalized severe COVID-19 patients: A 2-year follow-up study

Roles Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Software, Supervision, Validation, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Internal Medicine, St. Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia

Roles Data curation, Investigation, Project administration, Supervision, Validation, Writing – review & editing

Affiliation Department of Internal Medicine, Adera Medical and Surgical Center, Addis Ababa, Ethiopia

Roles Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Software, Supervision, Writing – original draft

Affiliation Department of Pediatrics, St. Peter’s Specialized Hospital, Addis Ababa, Ethiopia

Roles Investigation, Methodology, Project administration, Software, Validation, Writing – review & editing

Affiliation Department of Internal Medicine, Menelik II Specialized Hospital, Addis Ababa, Ethiopia

Roles Data curation, Formal analysis, Methodology, Writing – review & editing

Roles Data curation, Formal analysis, Investigation, Methodology, Software, Supervision, Validation, Writing – original draft

Affiliation Department of Research and Development, Deborah Foundation, Addis Ababa, Ethiopia

Roles Conceptualization, Methodology, Project administration, Software, Supervision, Validation, Writing – review & editing

Roles Data curation, Formal analysis, Methodology, Software, Writing – review & editing

Affiliation Department of Internal Medicine, Yekatit 12 Medical College, Addis Ababa, Ethiopia

Roles Conceptualization, Formal analysis, Investigation, Methodology, Writing – review & editing

• Tamrat Petros Elias, 
• Tsegaye Wesenseged Gebreamlak, 
• Tigist Tesfaye Gebremeskel, 
• Binyam Lukas Adde, 
• Abraham Sisay Abie, 
• Bitaniya Petros Elias, 
• Abel Mureja Argaw, 
• Addis Aschenek Tenaw, 
• Biruk Mulugeta Belay

• Published: May 10, 2024
• https://doi.org/10.1371/journal.pone.0298409
• Peer Review
• Reader Comments

Post-acute COVID-19 syndrome is a condition where individuals experience persistent symptoms after the acute phase of the COVID-19 infection has resolved, which lowers their quality of life and ability to return to work. This study assessed the prevalence and associated risk factors of post-acute COVID-19 syndrome (PACS) among severe COVID-19 patients who were discharged from Millennium COVID-19 Care Center, Addis Ababa, Ethiopia.

A cross-sectional study using data collected from patient charts and a follow-up telephone interview after two years of discharge. Systematic random sampling was used to select a total of 400 patients. A structured questionnaire developed from the case report form for PACS of the World Health Organization (WHO) was used. Frequency and cross-tabulation were used for descriptive statistics. Predictor variables with a p-value <0.25 in bivariate analyses were included in the logistic regression.

Out of the 400 patients, 20 patients were dead, 14 patients refused to give consent, and 26 patients couldn’t be reached because their phones weren’t working. Finally, 340 were included in the study. The majority (68.5%) were males and the mean age was 53.9 (±13.3 SD) years. More than a third (38.1%) of the patients reported the persistence of at least one symptom after hospital discharge. The most common symptoms were fatigue (27.5%) and Cough (15.3%). Older age (AOR 1.04, 95% CI 1.02–1.07), female sex (AOR 1.82, 95% CI 1.00–3.29), presence of comorbidity (AOR 2.38, 95% CI 1.35–4.19), alcohol use (AOR 3.05, 95% CI 1.49–6.26), fatigue at presentation (AOR 2.18, 95% CI 1.21–3.95), and longer hospital stay (AOR 1.06, 95% CI 1.02–1.10) were found to increase the odds of developing post-acute COVID-19 syndrome. Higher hemoglobin level was found to decrease the risk of subsequent post-acute COVID-19 syndrome (AOR 0.84, 95% CI 0.71–0.99).

The prevalence of post-acute COVID-19 syndrome is high, with a wide range of persistent symptoms experienced by patients. COVID-19 survivors with the identified risk factors are more susceptible to post-acute COVID-19 and require targeted monitoring and care in a multidisciplinary approach.

Citation: Elias TP, Gebreamlak TW, Gebremeskel TT, Adde BL, Abie AS, Elias BP, et al. (2024) Determinants of post-acute COVID-19 syndrome among hospitalized severe COVID-19 patients: A 2-year follow-up study. PLoS ONE 19(5): e0298409. https://doi.org/10.1371/journal.pone.0298409

Editor: Robert Jeenchen Chen, Stanford University School of Medicine, UNITED STATES

Received: September 13, 2023; Accepted: January 25, 2024; Published: May 10, 2024

Copyright: © 2024 Elias et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All raw data files are available from the Dryad repository database ( https://datadryad.org/stash/share/X4rfM77vUc2yRwvIi0mI9FiyXbIla0CzHgJJdwJTv5g ).

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

SARS-CoV-2, which causes coronavirus disease-19 (COVID-19), emerged as a public health threat in December 2019 [ 1 ]. According to the online World Health Organization (WHO) COVID-19 dashboard, as of May 1, 2023, the COVID-19 pandemic affected more than 765 million people and caused more than 6.9 million deaths globally [ 2 ]. The detection and treatment of acute illness does not appear to be the end of the COVID-19 fight. It has lately come to light that some patients’ incapacitating symptoms might last for weeks or even months [ 3 ]. This manifestation was termed ‘post-acute COVID-19 syndrome’, ‘post COVID conditions’, ‘chronic COVID-19’, or ‘long COVID’ [ 4 ]. The number of post-acute COVID-19 patients is rapidly increasing because millions of people have already contracted the disease and many more will do so in the future [ 5 ]. The capacity of people to return to work can be seriously impacted by persistent COVID-19 symptoms, with substantial psychological, social, and economic repercussions for those affected, their families, and society as a whole [ 6 ]. The annual economic impact of PACS (exclusive of costs of disability services, social services, and lost income on the part of caretakers) in the United States ranges from $140 billion to $600 billion [ 7 ].

The pathophysiology of PACS is multi-factorial and more than one mechanism may be implicated in several clinical manifestations. Immune dysregulation, persistent inflammatory reactions, autoimmune mimicry, pathogen reactivation, and host-microbiome changes may all play a role in the development of the syndrome [ 8 ]. Its pathophysiology is significantly influenced by prolonged inflammation, which can also be the cause of other symptoms such as cognitive impairment and neurological problems. Similar to multisystem inflammatory syndrome in children (MIS-C), a multisystem inflammatory syndrome in adults (MIS-A) of all ages has also been recently described [ 9 ].

The prevalence and clinical presentation of PACS is highly heterogeneous. The most frequently reported symptoms are fatigue, cardio-respiratory problems, and neurological symptoms [ 10 ]. There is a wide difference in the prevalence of post-acute COVID-19, from 46% in Bangladesh to 87.4% in Italy [ 11 , 12 ]. Some researchers concluded that female gender and older age are important risk factors for eventual PACS [ 13 , 14 ], but others, found no link between these sociodemographic characteristics and the development of PACS [ 15 ]. There is a significant difference in the works of literature on whether or not risk factors for developing PACS include the existence of comorbidities [ 13 , 16 ], the type of symptoms that present during an acute illness [ 15 , 17 ], the length of hospitalization [ 11 , 15 ], and the amount of oxygen needed upon admission [ 18 ]. Cigarette smoking was not associated with PACS in some studies [ 19 ], while others found a strong association [ 20 ].

Ethiopia notified the first confirmed case of COVID-19 on March 13, 2020 [ 21 ]. The country recorded the largest number of COVID-19 confirmed cases in East Africa [ 2 ], implying a large number of patients with PACS. There are no post-COVID clinics in Ethiopia, nor is there a documented guideline for the management of post-COVID sequelae. There were no research articles in peer-reviewed journals measuring the burden of PACS in Ethiopia at the time this study was conceived. To alleviate these issues, we need to understand the prevalence and risk factors of PACS to establish effective management measures such as rehabilitation and support services. This may include physical therapy, occupational therapy, cognitive interventions, and mental health support to address the diverse range of symptoms and disabilities experienced by individuals with PACS.

As a result, this study aimed to assess the prevalence and associated risk factors of PACS among severe COVID-19 patients who were discharged alive from Millennium COVID-19 Care and Treatment Center, Addis Ababa, Ethiopia between June 12, 2020, and November 1, 2021.

Methodology

Study design and setting.

A cross-sectional study design was used to assess the prevalence and associated risk factors of post-acute COVID-19 syndrome among severe COVID-19 patients who were discharged alive from Millennium COVID-19 Care Center, Addis Ababa, Ethiopia. Millennium COVID-19 Care Center (MCCC), was a makeshift hospital in Addis Ababa, the capital city of Ethiopia. The center was the biggest COVID-19 treatment facility in the country. It began giving service on June 2, 2020, and according to the center’s health management information system report (HMIS), as of November 1, 2021, a total of 6,760 patients were admitted and 5,580 patients were discharged alive.

Study participants

From adult patients (>18 years of age) who were admitted to MCCC with the diagnosis of Severe COVID-19 infection, confirmed by polymerase chain reaction (PCR) or rapid diagnostic test (RDT), those who were discharged alive between June 12, 2020, and November 1, 2021, were the study population.

Data collection tools and procedures

The socio-demographic profiles, past medical history including comorbidity, duration of symptoms before hospital admission, length of hospital stay, the maximum amount of oxygen required during hospital stay, acute manifestations of COVID-19, and baseline laboratory investigations were extracted from patient charts from January 2, 2023, to January 31, 2023. After obtaining verbal consent, a detailed telephonic interview was conducted with the study participants between February 1, 2023, and April 30, 2023, to record self-reported PACS symptoms and their characteristics, and self-assessment of current health status compared to the pre-COVID state. Data on COVID-19 vaccination history and current substance use were also collected during the telephone interview. The questionnaire was adapted from the W.H.O Global COVID-19 Clinical Platform Case Report Form (CRF) for Post COVID conditions (Post COVID-19 CRF) [ 22 ]. The English version of the questionnaire was first translated into Amharic, and a pilot study was done on 20 patients discharged from Eka Kotebe COVID-19 treatment center. A minor revision was made to the structure and language of the translated version based on the feedback from the participants in the pilot study. Data collectors were given training before the data collection. The collected data were entered into Epi-info software version 7 and then exported to Statistical Package for Social Sciences (SPSS) version 25 for cleaning and analysis. Individuals who could not be contacted after two attempts were excluded.

Sample size and statistical analysis

The sample size was determined for the prevalence by using the single population proportion formula and for the sociodemographic, clinical, and behavioral risk factors by using the double population proportion formula. The sample size calculated for the prevalence by using the single population proportion formula by considering p = 50%, as the prevalence of post-acute COVID syndrome is not known in Ethiopia, 95% confidence level (Zα/2 = 1.96), and a 5% margin of error yields the largest sample size. Since the source population is less than ten thousand (6760), a population correction formula was used and a 10% non-response rate was added to yield a final sample size of 400.

In this study, N (Study population) is 3576, and n (desired sample size) is 400. Using the above formula, k (sampling interval) is calculated to be 9. Every ninth patient discharged alive from MCCC with an admission diagnosis of severe COVID-19 and meeting the inclusion criteria is included in the study.

Frequency and cross-tabulation are used to summarize descriptive statistics of the data. The Mann–Whitney U test was used to compare skewed continuous variables. Associations between predictor variables and outcomes of interest are estimated using both bivariate analysis and binary logistic regression. Predictor variables with a p-value <0.25 in bivariate analyses are reported and included in the logistic regression. For the Binary Logistic regression, a 95% confidence interval for adjusted odds ratio (AOR) was calculated and variables with p-value ≤ 0.05 were considered as statistically associated with PACS.

Operational definitions

Severe covid-19..

Patients with clinical signs of severe pneumonia, ARDS, or sepsis ANDoxygen saturation less than 90% on room air; OR respiratory rate greater than 30.

Post-acute COVID-19 syndrome.

Persistence of any sign or symptom that was developed during the acute COVID-19 illness for more than twelve weeks after hospital discharge.

Ethical consideration

The study was conducted after obtaining ethical clearance from St. Paul’s Hospital Millennium Medical College Institutional Review Board. Verbal informed consent was taken from study participants during the telephone interview and documented on the questionnaire after explaining the purpose and objectives of the study. Confidentiality of individual patient information is maintained by using code numbers instead of other identifiers and the information gained from the chart and phone call is used only for research purposes.

Out of the 400 patients selected for the study, 20 patients (5%) died after hospital discharge, 14 patients (3.5%) refused to give consent, and 26 patients (6.5%) couldn’t be reached because their phone wasn’t working. The study included a total of 340 patients who were admitted to Millennium COVID-19 Care and Treatment Center with the diagnosis of severe COVID-19 pneumonia and discharged alive between June 12, 2020, and November 1, 2021 ( Fig 1 ). The mean duration from hospital discharge to the interview was 25.6 (± 4.8) months.

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https://doi.org/10.1371/journal.pone.0298409.g001

Baseline sociodemographic and clinical characteristics

The majority (68.5%) of the study participants were male and the remaining 31.5% were females. The mean age at the time of admission to the center was 53.9 (±13.3 SD) years. The minimum age was 22 years and the maximum age was 85 years.

More than half of the patients (60%) have one or more comorbidities. As shown in Table 1 , the most common comorbidity among the patients was diabetes (35.6%), followed by hypertension (34.1%), chronic heart disease (6.5%), asthma or COPD (5.6%), dyslipidemia (3.8%), HIV (3.2%), Cancer (1.5%), CLD (1.5%), stroke (1.2%), and CKD (0.3%).

https://doi.org/10.1371/journal.pone.0298409.t001

The median (IQR) duration of symptom onset before admission was 7 (5–10) days. The minimum was 1 day and the maximum was 30 days. The median (IQR) duration of hospital admission was 11 (7–15.75) days. The minimum was 2 days and the maximum was 39 days. The median (IQR) maximum amount of oxygen required during a hospital stay was 5 (3–7) liters. The minimum oxygen requirement was 1 liter and the maximum was 15 liters. A Mann-Whitney U test was conducted to compare the median scores of patients with and without PACS on duration of symptom onset before admission, length of hospital stay, and maximum amount of oxygen required during hospital stay. The test was statistically significant (p < 0.01) only for the length of hospital stay.

As shown in Table 2 , the most common symptoms at presentation were cough (93.5%), followed by shortness of breath (82.1%), and fatigue (69.7%).

https://doi.org/10.1371/journal.pone.0298409.t002

In the complete blood count (CBC) parameter of the patients, there were two outlier results recorded on patients with chronic lymphocytic leukemia (CLL), who had the white blood cell (WBC) count of 350,000 cells/ μL and 49,000 cells/ μL. The mean WBC count after excluding these two results was 9,148 (±4,044 SD) cells/ μL. The patients had a low mean lymphocyte percentage (10.2%). The mean hemoglobin was 14.6 (±1.7 SD) gm/dl and the mean platelet count was 285,840 (±116,588 SD) cells/ μL.

Current status of study participants

Most (67.8%) of study participants visited a health facility at least once after their discharge from Millennium COVID-19 care and treatment center. The most common reason (59%) for the health facility visit was for follow-up of chronic disease and 15.7% of the reasons for hospital visit after discharge were not feeling well.

More than a third (38.1%) of the patients reported the persistence of at least one symptom after hospital discharge. As shown in Table 3 , the most common symptoms that started during the acute COVID-19 infection and continued till the time of the interview in descending order were; fatigue (27.5%), Cough (15.3%), joint pain (14.1%), headache (11.9%), and shortness of breath (11.3%). Symptoms that were less commonly found were diarrhea (2.5%) and loss of appetite (2.5%).

https://doi.org/10.1371/journal.pone.0298409.t003

Close to one-third (29.4%) of the patients feel that their health condition has deteriorated after the COVID-19 infection. Forty-four (13.8%) of the patients claimed that, currently they are not able to do the daily activities they used to do before the infection which forced some of the patients to change and even quit their jobs. Currently, three (0.9%) and fifty-five (17.2%) of the patients smoke cigarettes and drink alcohol respectively. Of those who drink alcohol, most (40%) drink twice per month, followed by once per week (18.2%). Seven patients (12.7%) drink alcohol daily. Only 28.4% of the patients received at least one dose of vaccination.

Factors associated with PACS

Patient age, sex, presence of comorbidity, alcohol use, baseline hemoglobin level, initial presentation with fatigue or loss of appetite, and length of hospital stay were found to be associated with the development of PACS in the patients at a significant level of P <0.05. However, cigarette smoking, current vaccination status, mean day of presentation after symptom onset, and maximum amount of oxygen used during the hospital stay were not found to influence the development of post-acute COVID-19 syndrome ( Table 4 ).

https://doi.org/10.1371/journal.pone.0298409.t004

By using variables that have a p-value of <0.25 in the bivariate analysis, binary logisticregression was done after the model fitness test. Factors that were independently associated with the development of PACS were older age (AOR 1.04, 95% CI 1.02–1.07), female sex (AOR 1.82, 95% CI 1.00–3.29), presence of comorbidity (AOR 2.38, 95% CI 1.35–4.19), alcohol use (AOR 3.05, 95% CI 1.49–6.26), fatigue at presentation (AOR 2.18, 95% CI 1.21–3.95), and longer hospital stay (AOR 1.06, 95% CI 1.02–1.10). Higher hemoglobin level was found to decrease the risk of subsequent PACS (AOR 0.84, 95% CI 0.71–0.99) ( Table 5 ).

https://doi.org/10.1371/journal.pone.0298409.t005

As to the Authors’ knowledge, this is the first study that assessed the health consequences of COVID-19 at a two-year follow-up in patients who had severe COVID-19 pneumonia. 340 patients who were admitted to Millennium COVID-19 care and treatment center with the diagnosis of severe COVID-19 pneumonia were included in the study. The majority (68.5%) were males and the mean age was 53.9 (±13.3 SD) years. More than a third (38.1%) of the patients reported the persistence of at least one symptom after hospital discharge. The most common symptoms were fatigue (27.5%) and Cough (15.3%). Older age, female sex, presence of comorbidity, alcohol use, low baseline hemoglobin level, fatigue at presentation, and prolonged hospital stay were found to increase the odds of developing PACS. Thus, the study found that a significant proportion of patients don’t completely recover and continue to have some of the symptoms they developed during the acute infection.

The patients in this study were younger and males were more represented when compared to other similar studies. The mean age (53.9 years) at presentation was younger by six years in this study when compared to the cohort study conducted in Italy [ 20 ]. This is probably due to the demographic background of Ethiopia, where the proportion of the elderly population is lower than that in the Western world. The male-to-female ratio was 1.4:1 in the Bangladesh study, but the ratio is significantly higher (2.1:1) in this study [ 11 ].

The death rate after hospital discharge in this study was lower (5.8%) compared to a study done in Spain on patients who were admitted to Hospital for COVID-19. The study done in Spain found that 7.5% of the patients died within a mean follow-up period of one year [ 23 ].

The study participants in this study have a significantly higher level of comorbidity (60%) when compared to the cross-sectional study in Egypt on 430 patients found that 26.5% of patients reported that they have a chronic illness, and the Norwegian prospective cohort study, in which, 44% had comorbidities [ 16 , 24 ]. This significant difference in comorbidity is observed mainly because the other studies were done on all COVID-19 patients, and this study was done specifically on patients with severe COVID-19 pneumonia. Diabetes (35.6%), hypertension (34.1%), and chronic heart disease (6.5%) were the most common comorbidities in this study which is similar to the cohort studies done in Romania and England [ 25 , 26 ].

The prevalence of PACS in this study was 38.1%, which is lower than the finding in most of the studies, which were in the range of 46% in Bangladesh to 87.4% in Italy [ 11 , 12 ]. This may be because, in those studies, the maximum follow-up period was one year, but this study was conducted after a mean period of 25.6 months after hospital discharge and symptoms might have improved over time. The causes underlying these persistent symptoms following COVID-19 are not entirely understood. In addition to the direct effects of SARS-CoV-2, the immunological response to the virus is thought to have a role in the development of these long-term symptoms, presumably by supporting a continuing hyper-inflammatory process [ 27 ]. Molecular hydrogen inhalation had beneficial health effects in terms of improved physical (6-min walking test) and respiratory function in patients with PACS. Patients also noticed an improvement in fatigue after undergoing hyperbaric oxygen therapy and enhanced external counterpulsation. Muscle strength and physical function were improved after undergoing an 8-week biweekly physical therapy course including aerobic training, strengthening exercises, and diaphragmatic breathing techniques [ 28 ].

Fatigue is the most common (27.5%) symptom of PACS in this study, which is in concordance with the findings of most other similar studies [ 12 , 15 , 16 ]. Although the exact cause and pathogenesis of fatigue following COVID-19 is unknown, previous data from severe acute respiratory syndrome (SARS) suggests that lung diffusion capacity impairment, some extra-pulmonary causes, such as viral-induced myositis at initial presentation, cytokine disturbance, muscle wasting, and deconditioning, or corticosteroids myopathy, or a combination of these factors, may have contributed to the condition [ 29 ].

The second most common symptom in this study was cough (15.3%). This finding mirrors the findings of previous similar studies [ 11 , 19 , 30 ]. The mechanisms of cough after COVID-19 are multifactorial, including parenchymal sequelae and activation of the vagal sensory nerves, which leads to a cough hypersensitivity state [ 29 ].

In this study, 48% of female patients reported the presence of symptoms at the time of the interview. The female sex (AOR = 1.82, 95% CI 1.00–3.29, P = 0.04) was found to increase the risk of developing PACS. These findings are similar to other studies [ 13 , 14 ]. Various underlying processes explaining why females experience post-COVID symptoms to a larger extent than males are now being studied in the literature. Male and female biological differences in the expression of angiotensin-converting enzyme-2 (ACE2) and transmembrane protease serine 2 (TMPRSS2) receptors, as well as immunological differences, such as lower production of pro-inflammatory interleukin-6 (IL-6) after viral infection in females, could explain the higher development of post-COVID symptoms [ 31 ].

Older age (AOR = 1.04, 95% CI 1.02–1.07, P: <0.01) was found to be a statistically significant predictor for the development of PACS. This is a similar finding to a study done in France where older age increased the risk of subsequent PACS (AOR = 1.49, 95% CI 1.05–2.17) [ 17 ].

Unlike the Bangladesh cohort study which showed patients with fever, cough, respiratory distress, and lethargy as the presenting features were more susceptible to develop PACS compared to other presenting features and the Indian study which showed diarrhea at presentation to be associated with PACS, the only presenting feature that was found to be significant in this study was fatigue (AOR = 2.18, 95% CI 1.21–3.95, P: <0.01) [ 11 , 32 ].

In this study, prolonged hospital stay was found to significantly increase the risk of PACS (AOR = 1.06, 95% CI 1.02–1.10, P = 0.01). A similar finding was observed in a study conducted in Spain which revealed that the number of days at the hospital was significantly associated with an increased risk of PACS [ 33 ].

Although the number of days between symptom onset and admission in the Indian study and the amount of oxygen requirement in the Egyptian study was found to determine PACS, this study found no association between those factors and PACS [ 18 , 32 ].

Another finding in our study was that COVID-19 vaccination was not found to be protective from PACS. This was also shown in previous studies [ 34 ].

The studies on the effect of smoking as a risk factor for developing post-acute COVID-19 syndrome showed conflicting results. A study conducted in Egypt showed that there is no significant association between cigarette smoking and post-acute COVID-19 syndrome [ 18 ], while a study conducted in Italy found a strong association between current active smoking and post-acute COVID-19 syndrome [ 20 ]. This study found no significant association between current cigarette smoking and PACS.

The effect of alcohol intake on the development of PACS is found to be significant (AOR = 3.05 [1.49–6.26], P: <0.01) in this study, which is a similar finding to the Mediterranean cohort study and the Bangladesh study [ 11 , 15 ].

The study has certain limitations. This is a single-center cross-sectional study which makes generalization of the findings from this research difficult. The findings of this study might have also suffered from the fact that it is done via a telephone interview which relies on self-reporting and can be subject to recall bias. Furthermore, incomplete documentation on patient charts is another limitation. This study did not consider the broad range of patient characteristics because of the paucity of data. Mainly, nutritional status which was included in most other studies isn’t included in the analysis of this research because of incomplete documentation in most of the charts. Future research should consider longitudinal multi-center studies to enhance generalizability, employ diverse data collection methods, and use a larger sample size to ensure the robustness of the findings.

The prevalence of PACS syndrome among severe COVID-19 patients who were discharged alive from Millennium COVID-19 Care and Treatment Center between June 12, 2020, and November 15, 2021, after a mean period since discharge of 25.6 months, was found to be 38.1%. Fatigue (27.5%) and cough (15.3%) were the most prevalent symptoms. Older age, female sex, presence of comorbidity, alcohol use, low baseline hemoglobin level, fatigue at presentation, and prolonged hospital stay were found to increase the odds of developing PACS.

These risk factors provide valuable insights for healthcare professionals in identifying individuals who may be more susceptible to post-acute COVID-19 syndrome and require targeted monitoring and care. The research findings emphasize the critical importance of long-term healthcare management for COVID-19 survivors. Multidisciplinary approaches involving healthcare providers from various specialties will be crucial in providing holistic care to post-acute COVID-19 syndrome patients.

Acknowledgments

We would like to thank our research participants who made this research complete. We are also grateful to the management and staff of St. Paul’s Hospital Millennium Medical College for their cooperation.

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