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Does increased implementation support improve community clinics’ guideline-concordant care? Results of a mixed methods, pragmatic comparative effectiveness trial
Does increased implementation support improve community clinics’ guideline-concordant care? Results of a mixed methods, pragmatic comparative effectiveness trial
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Does increased implementation support improve community clinics’ guideline-concordant care? Results of a mixed methods, pragmatic comparative effectiveness trial
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Does increased implementation support improve community clinics’ guideline-concordant care? Results of a mixed methods, pragmatic comparative effectiveness trial
Does increased implementation support improve community clinics’ guideline-concordant care? Results of a mixed methods, pragmatic comparative effectiveness trial
Journal Article

Does increased implementation support improve community clinics’ guideline-concordant care? Results of a mixed methods, pragmatic comparative effectiveness trial

2019
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Overview
Background Disseminating care guidelines into clinical practice remains challenging, partly due to inadequate evidence on how best to help clinics incorporate new guidelines into routine care. This is particularly true in safety net community health centers (CHCs). Methods This pragmatic comparative effectiveness trial used a parallel mixed methods design. Twenty-nine CHC clinics were randomized to receive increasingly intensive implementation support (implementation toolkit (arm 1); toolkit + in-person training + training webinars (arm 2); toolkit + training + webinars + offered practice facilitation (arm 3)) targeting uptake of electronic health record (EHR) tools focused on guideline-concordant cardioprotective prescribing for patients with diabetes. Outcomes were compared across study arms, to test whether increased support yielded additive improvements, and with 137 non-study CHCs that share the same EHR as the study clinics. Quantitative data from the CHCs’ EHR were used to compare the magnitude of change in guideline-concordant ACE/ARB and statin prescribing, using adjusted Poisson regressions. Qualitative data collected using diverse methods (e.g., interviews, observations) identified factors influencing the quantitative outcomes. Results Outcomes at CHCs receiving higher-intensity support did not improve in an additive pattern. ACE/ARB prescribing did not improve in any CHC group. Statin prescribing improved overall and was significantly greater only in the arm 1 and arm 2 CHCs compared with the non-study CHCs. Factors influencing the finding of no additive impact included: aspects of the EHR tools that reduced their utility, barriers to providing the intended implementation support, and study design elements, e.g., inability to adapt the provided support. Factors influencing overall improvements in statin outcomes likely included a secular trend in awareness of statin prescribing guidelines, selection bias where motivated clinics volunteered for the study, and study participation focusing clinic staff on the targeted outcomes. Conclusions Efforts to implement care guidelines should: ensure adaptability when providing implementation support and conduct formative evaluations to determine the optimal form of such support for a given clinic; consider how study data collection influences adoption; and consider barriers to clinics’ ability to use/accept implementation support as planned. More research is needed on supporting change implementation in under-resourced settings like CHCs. Trial registration ClinicalTrials.gov , NCT02325531. Registered 15 December 2014.