An adaptable implementation package targeting evidence-based indicators in primary care: a pragmatic cluster-randomised evaluation

Background In primary care, multiple priorities and system pressures make closing the gap between evidence and practice challenging. Most implementation studies focus on single conditions, limiting generalisability. We compared an adaptable implementation package against an implementation control and assessed effects on adherence to four different evidence-based quality indicators. Methods and findings We undertook two parallel, pragmatic cluster-randomised trials using balanced incomplete block designs in general practices in West Yorkshire, England. We used ‘opt-out’ recruitment, and we randomly assigned practices that did not opt out to an implementation package targeting either diabetes control or risky prescribing (Trial 1); or blood pressure (BP) control or anticoagulation in atrial fibrillation (AF) (Trial 2). Within trials, each arm acted as the implementation control comparison for the other targeted indicator. For example, practices assigned to the diabetes control package acted as the comparison for practices assigned to the risky prescribing package. The implementation package embedded behaviour change techniques within audit and feedback, educational outreach, and computerised support, with content tailored to each indicator. Respective patient-level primary endpoints at 11 months comprised the following: achievement of all recommended levels of haemoglobin A1c (HbA1c), BP, and cholesterol; risky prescribing levels; achievement of recommended BP; and anticoagulation prescribing. Between February and March 2015, we recruited 144 general practices collectively serving over 1 million patients. We stratified computer-generated randomisation by area, list size, and pre-intervention outcome achievement. In April 2015, we randomised 80 practices to Trial 1 (40 per arm) and 64 to Trial 2 (32 per arm). Practices and trial personnel were not blind to allocation. Two practices were lost to follow-up but provided some outcome data. We analysed the intention-to-treat (ITT) population, adjusted for potential confounders at patient level (sex, age) and practice level (list size, locality, pre-intervention achievement against primary outcomes, total quality scores, and levels of patient co-morbidity), and analysed cost-effectiveness. The implementation package reduced risky prescribing (odds ratio [OR] 0.82; 97.5% confidence interval [CI] 0.67–0.99, p = 0.017) with an incremental cost-effectiveness ratio of £1,359 per quality-adjusted life year (QALY), but there was insufficient evidence of effect on other primary endpoints (diabetes control OR 1.03, 97.5% CI 0.89–1.18, p = 0.693; BP control OR 1.05, 97.5% CI 0.96–1.16, p = 0.215; anticoagulation prescribing OR 0.90, 97.5% CI 0.75–1.09, p = 0.214). No statistically significant effects were observed in any secondary outcome except for reduced co-prescription of aspirin and clopidogrel without gastro-protection in patients aged 65 and over (adjusted OR 0.62; 97.5% CI 0.39–0.99; p = 0.021). Main study limitations concern our inability to make any inferences about the relative effects of individual intervention components, given the multifaceted nature of the implementation package, and that the composite endpoint for diabetes control may have been too challenging to achieve. Conclusions In this study, we observed that a multifaceted implementation package was clinically and cost-effective for targeting prescribing behaviours within the control of clinicians but not for more complex behaviours that also required patient engagement. Trial registration The study is registered with the ISRCTN registry (ISRCTN91989345)

An exploration of patients’ experiences of participation in a randomised controlled trial of the Manchester Acute Coronary Syndromes (MACS) decision rule

Background As an important part of a pilot study to determine the feasibility of a large randomised controlled trial (RCT) comparing use of the Manchester Acute Coronary Syndromes (MACS) decision rule to standard care, we aimed to explore patient attitudes and potential barriers to participation in a trial of this nature. Methods We conducted a qualitative study nested within a pilot RCT comparing use of the MACS rule (which could enable some patients with chest pain to be discharged earlier) to standard care. Semi-structured interviews with consenting participants were conducted with reference to a bespoke topic guide. Interviews were audio recorded, transcribed verbatim and analysed using the Framework method with an inductive approach. Results The ten interviewees expressed that participation in the trial was generally acceptable. All but one recommended participation to others. Participants who were in pain or anxious at the time of arrival reported that the initial invitation to participate in the trial was sometimes made too early. The approach was welcome providing they had been given time to settle. Interviewees welcomed the opportunity that trial participation offered for them to play a more active role in their healthcare and to reduce unnecessary waiting time. Participants appeared to like that participation in the trial might mean they could return home sooner and welcomed the provision of follow-up. Although several participants described being generally sceptical of medical research, they were amenable to participation in this trial. This appears to be because they agreed with the need for research in this field and perceived the intervention as non-invasive. Conclusions Patients were positive about their participation in this RCT comparing the MACS rule to standard care. A number of areas for improving trial design were identified and should be considered in the planning of future large trial

Development of a Supported Self-management Intervention for People With Severe Mental Illness and Type 2 Diabetes: Theory and Evidence-Based Co-design Approach

BACKGROUND: Type 2 diabetes is 2 to 3 times more common among people with severe mental illness (SMI). Self-management is crucial, with additional challenges faced by people with SMI. Therefore, it is essential that any diabetes self-management program for people with SMI addresses the unique needs of people living with both conditions and the inequalities they experience within health care services. OBJECTIVE: We combined theory, empirical evidence, and co-design approaches to develop a type 2 diabetes self-management intervention for people with SMI. METHODS: The development process encompassed 4 steps: step 1 involved prioritizing the mechanisms of action (MoAs) and behavior change techniques (BCTs) for the intervention. Using findings from primary qualitative research and systematic reviews, we selected candidate MoAs to target in the intervention and candidate BCTs to use. Expert stakeholders then ranked these MoAs and BCTs using a 2-phase survey. The average scores were used to generate a prioritized list of MoAs and BCTs. During step 2, we presented the survey results to an expert consensus workshop to seek expert agreement with the definitive list of MoAs and BCTs for the intervention and identify potential modes of delivery. Step 3 involved the development of trigger films using the evidence from steps 1 and 2. We used animations to present the experiences of people with SMI managing diabetes. These films were used in step 4, where we used a stakeholder co-design approach. This involved a series of structured workshops, where the co-design activities were informed by theory and evidence. RESULTS: Upon the completion of the 4-step process, we developed the DIAMONDS (diabetes and mental illness, improving outcomes and self-management) intervention. It is a tailored self-management intervention based on the synthesis of the outputs from the co-design process. The intervention incorporates a digital app, a paper-based workbook, and one-to-one coaching designed to meet the needs of people with SMI and coexisting type 2 diabetes. CONCLUSIONS: The intervention development work was underpinned by the MoA theoretical framework and incorporated systematic reviews, primary qualitative research, expert stakeholder surveys, and evidence generated during co-design workshops. The intervention will now be tested for feasibility before undergoing a definitive evaluation in a pragmatic randomized controlled trial

Patients as qualitative data analysts: developing a method for a process evaluation of the ‘Improving the Safety and Continuity Of Medicines management at care Transitions’ (ISCOMAT) randomised controlled trial

Background How to meaningfully partner with patients as data analysts remains obscure. A process evaluation of the ‘Improving the Safety and Continuity Of Medicines management at care Transitions’ (ISCOMAT) cluster randomised control trial of an intervention for improving medicines use for people living with heart failure is being conducted. The intervention includes patient held information on heart medicines and care, enhanced communication between hospital and community pharmacists, and increased engagement of community pharmacists with patient care post‐hospital discharge. ISCOMAT patients living with heart failure were interviewed about experiences with the intervention. We sought to gain insights from patients on data collected to enhance our understanding of experiences with the intervention. Objective To develop a method for involving patients as analysts of qualitative data in a process evaluation. Design Patients and researchers co‐analysed qualitative data. A framework method was applied involving; familiarisation, coding, developing an analytical framework and interpretation. The process was facilitated through home working and a workshop with a training component. Results The co‐designed framework enabled researchers to map all further patient interview data. Patients' specialist knowledge enhanced understanding of how the ISCOMAT intervention can be best implemented. Conclusions Patients’ unique experiences can enhance validity and rigour in data analysis through sharing their interpretations of qualitative data. The involvement process is crucial in elucidating knowledge and avoiding tokenism. As analysts, patients gain an appreciation of research processes, building trust between researchers and patients. Group dynamics and involving patients throughout the whole research process are important considerations

Determinants of Physical Health Self-Management Behaviours in Adults With Serious Mental Illness:A Systematic Review

Behavioural interventions can support the adoption of healthier lifestyles and improve physical health outcomes, but it is unclear what factors might drive success of such interventions in people with serious mental illness (SMI). We systematically identified and reviewed evidence of the association between determinants of physical health self-management behaviours in adults with SMI. Data about American Association of Diabetes Educator’s Self-Care Behaviours (AADE-7) were mapped against the novel Mechanisms of Action (MoA) framework. Twenty-eight studies were included in the review, reporting evidence on 104 determinant-behaviour links. Beliefs about capabilities and beliefs about consequences were the most important determinants of behaviour, especially for being physically active and healthy eating. There was some evidence that emotion and environmental context and resources played a role in determining reducing risks, being active, and taking medications. We found very limited evidence associated with problem solving, and no study assessed links between MoAs and healthy coping. Although the review predominantly identified evidence about associations from cross-sectional studies that lacked validated and objective measures of self-management behaviours, these findings can facilitate the identification of behaviour change techniques with hypothesised links to determinants to support self-management in people with SMI

Exploring severe mental illness and diabetes : protocol for a longitudinal observational and qualitative mixed methods study

Background: The average life expectancy for people with a severe mental illness (SMI) such as schizophrenia or bipolar disorder is 15-20 years less than for the population as a whole. Diabetes contributes significantly to this inequality, being 2-3 times more prevalent in people with SMI. Various risk factors have been implicated, including side effects of antipsychotic medication and unhealthy lifestyles, which often occur in the context of socio-economic disadvantage and healthcare inequality. However, little is known about how these factors interact to influence the risk of developing diabetes and poor diabetic outcomes, or how the organisation and provision of healthcare may contribute. Objective: The study aims to identify the determinants of diabetes and to explore variation in diabetes outcomes for people with SMI. Methods: This study will employ a concurrent mixed methods design combining the interrogation of electronic primary care health records from the Clinical Practice Research Datalink (CPRD GOLD) with qualitative interviews with adults with SMI and diabetes, their relatives/friends, and healthcare staff. The study has been funded for two years, from September 2017 to September 2019 and data collection has recently ended. Results: CPRD and linked health data will be used to explore the association of socio-demographic, illness and healthcarerelated factors with both the development and outcomes of Type 2 diabetes in people with SMI. Experiences of managing the comorbidity and accessing healthcare will be explored through qualitative interviews using topic guides informed by evidence synthesis and expert consultation. Findings from both datasets will be merged to develop a more comprehensive understanding of diabetes risks, interventions and outcomes for people with SMI. Findings will be translated into recommendations for interventions and services using co-design workshops. Conclusions: Improving diabetes outcomes for people with SMI is a high priority area nationally and globally. Understanding how risk factors combine to generate high prevalence of diabetes and poor diabetic outcomes for this population is a necessary first step in developing healthcare interventions to improve outcomes for people with diabetes and SMI