Mei-See Man

Objective Patients with multiple chronic health conditions are often managed in a disjointed fashion in primary care, with annual review clinic appointments offered separately for each condition. This study aimed to determine the cost-effectiveness of the 3D intervention, which was developed to improve the system of care. Design Economic evaluation conducted alongside a pragmatic cluster-randomised trial. Setting General practices in three centres in England and Scotland. Participants 797 adults with three or more chronic conditions were randomised to the 3D intervention, while 749 participants were randomised to receive usual care. Intervention The 3D approach: comprehensive 6-monthly general practitioner consultations, supported by medication reviews and nurse appointments. Primary and secondary outcome measures The primary economic evaluation assessed the cost per quality-adjusted life year (QALY) gained from the perspective of the National Health Service (NHS) and personal social services (PSS). Costs were related to changes in a range of secondary outcomes (QALYs accrued by both participants and carers, and deaths) in a cost–consequences analysis from the perspectives of the NHS/PSS, patients/carers and productivity losses. Results Very small increases were found in both QALYs (adjusted mean difference 0.007 (−0.009 to 0.023)) and costs (adjusted mean difference £126 (£−739 to £991)) in the intervention arm compared with usual care after 15 months. The incremental cost-effectiveness ratio was £18 499, with a 50.8% chance of being cost-effective at a willingness-to-pay threshold of £20 000 per QALY (55.8% at £30 000 per QALY). Conclusions The small differences in costs and outcomes were consistent with chance, and the uncertainty was substantial; therefore, the evidence for the cost-effectiveness of the 3D approach from the NHS/PSS perspective should be considered equivocal. Trial registration number ISCRTN06180958

Objectives During a cluster randomised trial, (the 3D study) of an intervention enacting recommended care for people with multimorbidity, including continuity of care and comprehensive biennial reviews, we examined implementation fidelity to interpret the trial outcome and inform future implementation decisions. Design Mixed-methods process evaluation using cross-trial data and a sample of practices, clinicians, administrators and patients. Interviews, focus groups and review observations were analysed thematically and integrated with quantitative data about implementation. Analysis was blind to trial outcomes and examined context, intervention adoption, reach and maintenance, and delivery of reviews to patients. Setting Thirty-three UK general practices in three areas. Participants The trial included 1546 people with multimorbidity. 11 general practitioners, 14 nurses, 7 administrators and 38 patients from 9 of 16 intervention practices were sampled for an interview. Results Staff loss, practice size and different administrative strategies influenced implementation fidelity. Practices with whole administrative team involvement and good alignment between the intervention and usual care generally implemented better. Fewer reviews than intended were delivered (49% of patients receiving both intended reviews, 30% partially reviewed). In completed reviews >90% of intended components were delivered, but review observations and interviews with patients and clinicians found variation in style of component delivery, from ‘tick-box’ to patient-centred approaches. Implementation barriers included inadequate skills training to implement patient-centred care planning, but patients reported increased patient-centredness due to comprehensive reviews, extra time and being asked about their health concerns. Conclusions Implementation failure contributed to lack of impact of the 3D intervention on the trial primary outcome (quality of life), but so did intervention failure since modifiable elements of intervention design were partially responsible. When a decisive distinction between implementation failure and intervention failure cannot be made, identifying potentially modifiable reasons for suboptimal implementation is important to enhance potential for impact and effectiveness of a redesigned intervention. Trial registration number ISRCTN06180958

Background: People with multimorbidity experience impaired quality of life, poor health and a burden from treatment. Their care is often disease-focused rather than patient-centred and tailored to their individual needs.Objective: To implement and evaluate a patient-centred intervention to improve the management of patients with multimorbidity in general practice.Design: Pragmatic, cluster randomised controlled trial with parallel process and economic evaluations. Practices were centrally randomised by a statistician blind to practice identifiers, using a computer-generated algorithm.Setting: Thirty-three general practices in three areas of England and Scotland.Participants: Practices had at least 4500 patients and two general practitioners (GPs) and used the EMIS (Egton Medical Information Systems) computer system. Patients were aged ≥ 18 years with three or more long-term conditions.Interventions: The 3D (Dimensions of health, Depression and Drugs) intervention was designed to offer patients continuity of care with a named GP, replacing separate reviews of each long-term condition with comprehensive reviews every 6 months. These focused on individualising care to address patients’ main problems, attention to quality of life, depression and polypharmacy and on disease control and agreeing treatment plans. Control practices provided usual care.Outcome measures: Primary outcome – health-related quality of life (assessed using the EuroQol-5 Dimensions, five-level version) after 15 months. Secondary outcomes – measures of illness burden, treatment burden and patient-centred care. We assessed cost-effectiveness from a NHS and a social care perspective.Results: Thirty-three practices (1546 patients) were randomised from May to December 2015 [16 practices (797 patients) to the 3D intervention, 17 practices (749 patients) to usual care]. All participants were included in the primary outcome analysis by imputing missing data. There was no evidence of difference between trial arms in health-related quality of life {adjusted difference in means 0.00 [95% confidence interval (CI) –0.02 to 0.02];p = 0.93}, illness burden or treatment burden. However, patients reported significant benefits from the 3D intervention in all measures of patient-centred care. Qualitative data suggested that both patients and staff welcomed having more time, continuity of care and the patient-centred approach. The economic analysis found no meaningful differences between the intervention and usual care in either quality-adjusted life-years [(QALYs) adjusted mean QALY difference 0.007, 95% CI –0.009 to 0.023] or costs (adjusted mean difference £126, 95% CI –£739 to £991), with wide uncertainty around point estimates. The cost-effectiveness acceptability curve suggested that the intervention was unlikely to be either more or less cost-effective than usual care. Seventy-eight patients died (46 in the intervention arm and 32 in the usual-care arm), with no evidence of difference between trial arms; no deaths appeared to be associated with the intervention.Limitations: In this pragmatic trial, the implementation of the intervention was incomplete: 49% of patients received two 3D reviews over 15 months, whereas 75% received at least one review.Conclusions: The 3D approach reflected international consensus about how to improve care for multimorbidity. Although it achieved the aim of providing more patient-centred care, this was not associated with benefits in quality of life, illness burden or treatment burden. The intervention was no more or less cost-effective than usual care. Modifications to the 3D approach might improve its effectiveness. Evaluation is needed based on whole-system change over a longer period of time.Trial registration: Current Controlled Trials ISRCTN06180958.Funding: This project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full inHealth Services and Delivery Research; Vol. 7, No. 5. See the NIHR Journals Library website for further project information.

Objectives Recent evidence has highlighted the high prevalence and impact of multimorbidity, but the evidence base for improving management is limited. We have tested a new complex intervention for multimorbidity (the 3D model). The paper describes the baseline characteristics of practices and patients in order to establish the external validity of trial participants. It also explores current ‘usual primary care’ for multimorbidity, against which the 3D intervention was tested. Design Analysis of baseline data from patients in a cluster-randomised controlled trial and additional data from practice staff. Setting Primary care in the UK. Participants Patients with multimorbidity (n=5253) and 154 practice staff. Primary and secondary outcome measures Using surveys and routinely available data, we compared the characteristics of participating and non-participating practices and participating and non-participating eligible patients. Baseline questionnaire data from patient participants was used to examine participant illness burden, treatment burden and perceptions of receiving patient-centred care. We obtained data about usual care preintervention from practice staff using questionnaires and a structured pro forma. Results Participating practices were slightly larger, in less deprived areas, and with slightly higher scores for patient satisfaction compared with non-participating practices. Patients with dementia or learning difficulties were likely to be excluded by their general practitioners, but comparison of participants with non-participants identified only minor differences in characteristics, suggesting that the sample was otherwise representative. Patients reported substantial illness burden, and an important minority reported high treatment burden. Although patients reported relatively high levels of satisfaction with care, many reported not having received potentially important components of care. Conclusion This trial achieved good levels of external validity. Although patients were generally satisfied with primary care services, there was significant room for improvement in important aspects of care for multimorbidity that are targeted by the 3D intervention. Trial registration number ISRCTN06180958; Post-results.

Including patient and public involvement (PPI) in health research is thought to improve research but it is hard to be clear exactly how it helps. This is because PPI takes many forms, is sometimes only token and is not always reported clearly. This makes it difficult to combine the evidence so that clear conclusions can be reached about the ingredients of successful PPI and what PPI achieves. Previous research that has tried to combine the evidence has led to several guidelines for researchers to use in setting up and reporting PPI. This paper was written jointly by researchers and PPI contributors as a reflection on our experiences. The aim was to add to the evidence, by giving detail about the use of PPI in a large randomised controlled trial and the effect it had. We were guided by published PPI reporting guidelines. The effects on the trial are shown in a table of changes made because of suggestions from the PPI group. A survey was used to ask PPI contributors and researchers about their experience and effects they had noticed. Three themes were noted: impact on the trial, the effect of involvement on individual researchers and group members, and group environment. The PPI work affected the trial in many ways, including changes to documents used in the trial and advice on qualitative data collection methods and analysis. Individuals reported positive effects, including enjoying being in the group, gaining confidence, and learning how to share views. Patient and public involvement (PPI) is believed to enhance health care delivery research, and is widely required in research proposals. Detailed, standardised reporting of PPI is needed so that strategies to implement more than token PPI that achieves impact can be identified, properly evaluated and reproduced. Impact includes effects on the research, PPI contributors and researchers. Using contributor and researcher perspectives and drawing on published guidelines for reporting PPI, we aimed to reflect on our experience and contribute evidence relevant to two important questions: ‘What difference does PPI make?’ and ‘What’s the best way to do it?’ Fourteen people living with multiple long-term conditions (multimorbidity) were PPI contributors to a randomised controlled trial to improve care for people with multimorbidity. Meetings took place approximately four times a year throughout the trial, beginning at grant application stage. Meeting notes were recorded and a log of PPI involvement was kept. At the end of the trial, seven PPI contributors and four researchers completed free-text questionnaires about their experience of PPI involvement and their perception of PPI impact. The responses were analysed thematically by two PPI contributors and one researcher. The PPI group proposed writing this report, which was co-authored by three PPI contributors and two researchers. Meeting attendance averaged nine PPI contributors and three to four researchers. The involvement log and meeting notes recorded a wide range of activities and impact including changes to participant documentation, advice on qualitative data collection, contribution to data analysis and dissemination advice. Three themes were identified from the questionnaires: impact on the study, including keeping the research grounded in patient experience; impact on individuals, including learning from group diversity and feeling valued; and an environment that facilitated participation. The size of the group influenced impact. Researchers and PPI contributors described a rewarding interaction that benefitted them and the research. PPI was wide-ranging and had impact on the trial, contributors and researchers. The group environment facilitated involvement. Feedback and group interactions benefitted individuals. The insights gained from this study will postitively influence the researchers’ and contributors’ future involvement with PPI.

Objective: To develop and validate a new scale to assess treatment burden (the effort of looking after one’s health) for patients with multimorbidity. Design: Mixed-methods. Setting: UK primary care. Participants: Content of the Multimorbidity Treatment Burden Questionnaire (MTBQ) was based on a literature review and views from a patient and public involvement group. Face validity was assessed through cognitive interviews. The scale was piloted and the final version was tested in 1546 adults with multimorbidity (mean age 71 years) who took part in the 3D Study, a cluster randomised controlled trial. For each question, we examined the proportion of missing data and the distribution of responses. Factor analysis, Cronbach’s alpha, Spearman’s rank correlations and longitudinal regression assessed dimensional structure, internal consistency reliability, construct validity and responsiveness, respectively. We assessed interpretability by grouping the global MTBQ scores into zero and tertiles (>0) and comparing participant characteristics across these categories. Results: Cognitive interviews found good acceptability and content validity. Factor analysis supported a one-factor solution. Cronbach’s alpha was 0.83, indicating internal consistency reliability. The MTBQ score had a positive association with a comparator treatment burden scale (r_s0.58, Ps0.43, Ps−0.36, Ps−0.36, P<0.0001). Female participants, younger participants and participants with mental health conditions were more likely to have high treatment burden scores. Changes in MTBQ score over 9-month follow-up were associated, as expected, with changes in measures of quality of life (EuroQol five dimensions, five level questionnaire) and patient-centred care (Patient Assessment of Chronic Illness Care). Conclusion: The MTBQ is a 10-item measure of treatment burden for patients with multimorbidity that has demonstrated good content validity, construct validity, reliability and responsiveness. It is a useful research tool for assessing the impact of interventions on treatment burden. Trial registration number: NCT06180958.

PURPOSE Multimorbidity challenges health systems globally. New models of care are urgently needed to better manage patients with multimorbidity; however, there is no agreed framework for designing and reporting models of care for multimorbidity and their evaluation. METHODS Based on findings from a literature search to identify models of care for multimorbidity, we developed a framework to describe these models. We illustrate the application of the framework by identifying the focus and gaps in current models of care, and by describing the evolution of models over time. RESULTS Our framework describes each model in terms of its theoretical basis and target population (the foundations of the model) and of the elements of care implemented to deliver the model. We categorized elements of care into 3 types: (1) clinical focus, (2) organization of care, (3) support for model delivery. Application of the framework identified a limited use of theory in model design and a strong focus on some patient groups (elderly, high users) more than others (younger patients, deprived populations). We found changes in elements with time, with a decrease in models implementing home care and an increase in models offering extended appointments. CONCLUSIONS By encouragin greater clarity about the underpinning theory and target population, and by categorizing the wide range of potentially important elements of an intervention to improve care for patients with multimorbidity, the framework may be useful in designing and reporting models of care and help advance the currently limited evidence base.