The Invested in Diabetes Study Protocol: a cluster randomized pragmatic trial comparing standardized and patient-driven diabetes shared medical appointments

Collaborative care approaches for people with severe mental illness

BACKGROUND

Collaborative care for severe mental illness (SMI) is a community-based intervention that promotes interdisciplinary working across primary and secondary care. Collaborative care interventions aim to improve the physical and/or mental health care of individuals with SMI. This is an update of a 2013 Cochrane review, based on new searches of the literature, which includes an additional seven studies.

OBJECTIVES

To assess the effectiveness of collaborative care approaches in comparison with standard care (or other non-collaborative care interventions) for people with diagnoses of SMI who are living in the community.

SEARCH METHODS

We searched the Cochrane Schizophrenia Study-Based Register of Trials (10 February 2021). We searched the Cochrane Common Mental Disorders (CCMD) controlled trials register (all available years to 6 June 2016). Subsequent searches on Ovid MEDLINE, Embase and PsycINFO together with the Cochrane Central Register of Controlled Trials (with an overlap) were run on 17 December 2021.

SELECTION CRITERIA

Randomised controlled trials (RCTs) where interventions described as 'collaborative care' were compared with 'standard care' for adults (18+ years) living in the community with a diagnosis of SMI. SMI was defined as schizophrenia, other types of schizophrenia-like psychosis or bipolar affective disorder. The primary outcomes of interest were: quality of life, mental state and psychiatric admissions at 12 months follow-up.

DATA COLLECTION AND ANALYSIS

Pairs of authors independently extracted data. We assessed the quality and certainty of the evidence using RoB 2 (for the primary outcomes) and GRADE. We compared treatment effects between collaborative care and standard care. We divided outcomes into short-term (up to six months), medium-term (seven to 12 months) and long-term (over 12 months). For dichotomous data we calculated the risk ratio (RR) and for continuous data we calculated the standardised mean difference (SMD), with 95% confidence intervals (CIs). We used random-effects meta-analyses due to substantial levels of heterogeneity across trials. We created a summary of findings table using GRADEpro.

MAIN RESULTS

Eight RCTs (1165 participants) are included in this review. Two met the criteria for type A collaborative care (intervention comprised of the four core components). The remaining six met the criteria for type B (described as collaborative care by the trialists, but not comprised of the four core components). The composition and purpose of the interventions varied across studies. For most outcomes there was low- or very low-certainty evidence. We found three studies that assessed the quality of life of participants at 12 months. Quality of life was measured using the SF-12 and the WHOQOL-BREF and the mean endpoint mental health component scores were reported at 12 months. Very low-certainty evidence did not show a difference in quality of life (mental health domain) between collaborative care and standard care in the medium term (at 12 months) (SMD 0.03, 95% CI -0.26 to 0.32; 3 RCTs, 227 participants). Very low-certainty evidence did not show a difference in quality of life (physical health domain) between collaborative care and standard care in the medium term (at 12 months) (SMD 0.08, 95% CI -0.18 to 0.33; 3 RCTs, 237 participants). Furthermore, in the medium term (at 12 months) low-certainty evidence did not show a difference between collaborative care and standard care in mental state (binary) (RR 0.99, 95% CI 0.77 to 1.28; 1 RCT, 253 participants) or in the risk of being admitted to a psychiatric hospital at 12 months (RR 5.15, 95% CI 0.67 to 39.57; 1 RCT, 253 participants). One study indicated an improvement in disability (proxy for social functioning) at 12 months in the collaborative care arm compared to usual care (RR 1.38, 95% CI 0.97 to 1.95; 1 RCT, 253 participants); we deemed this low-certainty evidence. Personal recovery and satisfaction/experience of care outcomes were not reported in any of the included studies. The data from one study indicated that the collaborative care treatment was more expensive than standard care (mean difference (MD) international dollars (Int$) 493.00, 95% CI 345.41 to 640.59) in the short term. Another study found the collaborative care intervention to be slightly less expensive at three years.

AUTHORS' CONCLUSIONS

This review does not provide evidence to indicate that collaborative care is more effective than standard care in the medium term (at 12 months) in relation to our primary outcomes (quality of life, mental state and psychiatric admissions). The evidence would be improved by better reporting, higher-quality RCTs and the assessment of underlying mechanisms of collaborative care. We advise caution in utilising the information in this review to assess the effectiveness of collaborative care.

A Multi-Method Study of Patient Reach and Attendance in a Pragmatic Trial of Diabetes Shared Medical Appointments

Shared medical appointments (SMAs) are an evidence-based approach to diabetes care in primary care settings, yet practices can struggle to ensure participation, especially among racial and ethnic minority and low-income patients. We conducted a multimethod evaluation of reach and attendance in the Invested in Diabetes study of the comparative effectiveness of two SMA delivery models (standardized and patient-driven) in two practice settings (federally qualified health centers [FQHCs] and clinics serving more commercially insured patients). Through this study, 22 practices reached 6.2% of patients with diabetes through SMAs over 3 years, with good attendance for both practice types and both SMA delivery models. FQHCs were especially successful at enrolling underserved populations and improved attendance with virtual SMAs.

Delivering diabetes shared medical appointments in primary care: early and mid-program adaptations and implications for successful implementation

BACKGROUND

Self-management is essential for good outcomes in type 2 diabetes and patients often benefit from self-management education. Shared medical appointments (SMAs) can increase self-efficacy for self management but are difficult for some primary care practices to implement. Understanding how practices adapt processes and delivery of SMAs for patients with type 2 diabetes may provide helpful strategies for other practices interested in implementing SMAs.

METHODS

The Invested in Diabetes study was a pragmatic cluster-randomized, comparative effectiveness trial designed to compare two different models of diabetes SMAs delivered in primary care. We used a multi-method approach guided by the FRAME to assess practices' experience with implementation, including any planned and unplanned adaptations. Data sources included interviews, practice observations and field notes from practice facilitator check-ins.

RESULTS

Several findings were identified from the data: 1) Modifications and adaptations are common in implementation of SMAs, 2) while most adaptations were fidelity-consistent supporting the core components of the intervention conditions as designed, some were not, 3) Adaptations were perceived to be necessary to help SMAs meet patient and practice needs and overcome implementation challenges, and 4) Content changes in the sessions were often planned and enacted to better address the contextual circumstances such as patient needs and culture.

DISCUSSION

Implementing SMAs in primary care can be challenging and adaptations of both implementation processes and content and delivery of SMAS for patients with type 2 diabetes were common in the Invested in Diabetes study. Recognizing the need for adaptations based on practice context prior to implementation may help improve fit and success with SMAs, but care needs to be given to ensure that adaptations do not weaken the impact of the intervention. Practices may be able to assess what might need to adapted for them to be successful prior to implementation but likely will continue to adapt after implementation.

CONCLUSION

Adaptations were common in the Invested in Diabetes study. Practices may benefit from understanding common challenges in implementing SMAs and adapting processes and delivery based on their own context.

TRIAL REGISTRATION

This trial is registered on clinicaltrials.gov under Trial number NCT03590041, posted 18/07/2018.

Methods for capturing and analyzing adaptations: implications for implementation research

Background

Interventions are often adapted; some adaptations may provoke more favorable outcomes, whereas some may not. A better understanding of the adaptations and their intended goals may elucidate which adaptations produce better outcomes. Improved methods are needed to better capture and characterize the impact of intervention adaptations.

Methods

We used multiple data collection and analytic methods to characterize adaptations made by practices participating in a hybrid effectiveness-implementation study of a complex, multicomponent diabetes intervention. Data collection methods to identify adaptations included interviews, observations, and facilitator sessions resulting in transcripts, templated notes, and field notes. Adaptations gleaned from these sources were reduced and combined; then, their components were cataloged according to the framework for reporting adaptations and modifications to evidence-based interventions (FRAME). Analytic methods to characterize adaptations included a co-occurrence table, statistically based k-means clustering, and a taxonomic analysis.

Results

We found that (1) different data collection methods elicited more overall adaptations, (2) multiple data collection methods provided understanding of the components of and reasons for adaptation, and (3) analytic methods revealed ways that adaptation components cluster together in unique patterns producing adaptation “types.” These types may be useful for understanding how the “who, what, how, and why” of adaptations may fit together and for analyzing with outcome data to determine if the adaptations produce more favorable outcomes rather than by adaptation components individually.

Conclusion

Adaptations were prevalent and discoverable through different methods. Enhancing methods to describe adaptations may better illuminate what works in providing improved intervention fit within context.

Trial registration

This trial is registered on clinicaltrials.gov under Trial number NCT03590041, posted July 18, 2018.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13012-022-01218-3.

Protocol refinement for a diabetes pragmatic trial using the PRECIS-2 framework

Background

This report describes how we refined a protocol for a pragmatic comparative effectiveness study of two models of an evidence-based diabetes shared medical appointment intervention and used the PRECIS-2 rating system to evaluate these adaptations.

Methods

We report primary data collected between June and August 2019, and protocol refinements completed between 2018 and 2020. Twenty-two members of the study team collaborated in protocol refinement and completed the PRECIS-2 ratings of study pragmatism. We discuss study design refinements made to achieve the desired level of pragmatism vs. experimental control for each of the nine PRECIS-2 dimensions. Study team members received training on PRECIS-2 scoring and were asked to rate the study protocol on the nine PRECIS-2 dimensions. Ratings were compared using descriptive statistics.

Results

In general, the PRECIS-2 ratings revealed high levels of pragmatism, but somewhat less pragmatic ratings on the categories of Delivery and Organization (costs and resources). This variation was purposeful, and we provide the rationale for and steps taken to obtain the targeted level of pragmatism on each PRECIS-2 dimension, as well as detail design changes made to a) make the design more pragmatic and b) address COVID-19 issues. There was general agreement among team members and across different types of stakeholders on PRECIS-2 ratings.

Conclusions

We discuss lessons learned from use of PRECIS-2 and experiences in refining the study to be maximally pragmatic on some dimensions and less so on other dimensions. This paper expands on prior research by describing actions to achieve higher levels of pragmatism and revise our protocol fit to the changed context. We make recommendations for future use of PRECIS-2 to help address changing context and other strategies for the planning of and transparent reporting on pragmatic research and comparative effectiveness research.

Trial registration

Clinicaltrials.gov Registration ID: NCT03590041.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07084-x.

Evaluating the Effectiveness of Diabetes Shared Medical Appointments (SMAs) as Implemented in Five Veterans Affairs Health Systems: a Multi-site Cluster Randomized Pragmatic Trial

OBJECTIVE

To examine whether diabetes shared medical appointments (SMAs) implemented as part of usual clinical practice in diverse health systems are more effective than usual care in improving and sustaining A1c improvements.

RESEARCH DESIGN AND METHODS

A multi-site cluster randomized pragmatic trial examining implementation in clinical practice of diabetes SMAs in five Veterans Affairs (VA) health systems was conducted from 2016 to 2020 among 1537 adults with type 2 diabetes and elevated A1cs. Eligible patients were randomly assigned to either: (1) invitation to participate in a series of SMAs totaling 8-9 h; or (2) continuation of usual care. Relative change in A1c (primary outcome) and in systolic blood pressure, insulin starts, statin starts, and anti-hypertensive medication classes (secondary outcomes) were measured as part of usual clinical care at baseline, at 6 months and at 12 months (~7 months after conclusion of the final SMA in four of five sites). We examined outcomes in three samples of SMA participants: all those scheduled for a SMA, those attending at least one SMA, and those attending at least half of SMAs.

RESULTS

Baseline mean A1c was 9.0%. Participants scheduled for an SMA achieved A1c reductions 0.35% points greater than the control group between baseline and 6-months follow up (p = .001). Those who attended at least one SMA achieved reductions 0.42 % points greater (p < .001), and those who attended at least half of scheduled SMAs achieved reductions 0.53 % points greater (p < .001) than the control group. At 12-month follow-up, the three SMA analysis samples achieved reductions from baseline ranging from 0.16 % points (p = 0.12) to 0.29 % points (p = .06) greater than the control group.

CONCLUSIONS

Diabetes SMAs as implemented in real-life diverse clinical practices improve glycemic control more than usual care immediately after the SMAs, but relative gains are not maintained. Our findings suggest the need for further study of whether a longer term SMA model or other follow-up strategies would sustain relative clinical improvements associated with this intervention.

TRIAL REGISTRATION

ClinicalTrials.gov ID NCT02132676.

Correction to: The Invested in Diabetes Study Protocol: a cluster randomized pragmatic trial comparing standardized and patient-driven diabetes shared medical appointments

After publication of our article [1] the authors have notified us that the title for Figure 1 was incorrectly captioned.