%0 Journal Article
%@ 1438-8871
%I JMIR Publications
%V 23
%N 12
%P e31042
%T Measuring and Improving Evidence-Based Patient Care Using a Web-Based Gamified Approach in Primary Care (QualityIQ): Randomized Controlled Trial
%A Burgon,Trever
%A Casebeer,Linda
%A Aasen,Holly
%A Valdenor,Czarlota
%A Tamondong-Lachica,Diana
%A de Belen,Enrico
%A Paculdo,David
%A Peabody,John
%+ QURE Healthcare, 450 Pacific Ave, Suite 200, San Francisco, CA, 94133, United States, 1 4153213388 ext 101, jpeabody@qurehealthcare.com
%K quality improvement
%K physician engagement
%K MIPS
%K case simulation
%K feedback
%K value-based care
%K care standardization
%K simulation
%K gamification
%K medical education
%K continuing education
%K outcome
%K serious game
%K decision-support
%D 2021
%7 23.12.2021
%9 Original Paper
%J J Med Internet Res
%G English
%X Background: Unwarranted variability in clinical practice is a challenging problem in practice today, leading to poor outcomes for patients and low-value care for providers, payers, and patients. Objective: In this study, we introduced a novel tool, QualityIQ, and determined the extent to which it helps primary care physicians to align care decisions with the latest best practices included in the Merit-Based Incentive Payment System (MIPS). Methods: We developed the fully automated QualityIQ patient simulation platform with real-time evidence-based feedback and gamified peer benchmarking. Each case included workup, diagnosis, and management questions with explicit evidence-based scoring criteria. We recruited practicing primary care physicians across the United States into the study via the web and conducted a cross-sectional study of clinical decisions among a national sample of primary care physicians, randomized to continuing medical education (CME) and non-CME study arms. Physicians “cared” for 8 weekly cases that covered typical primary care scenarios. We measured participation rates, changes in quality scores (including MIPS scores), self-reported practice change, and physician satisfaction with the tool. The primary outcomes for this study were evidence-based care scores within each case, adherence to MIPS measures, and variation in clinical decision-making among the primary care providers caring for the same patient. Results: We found strong, scalable engagement with the tool, with 75% of participants (61 non-CME and 59 CME) completing at least 6 of 8 total cases. We saw significant improvement in evidence-based clinical decisions across multiple conditions, such as diabetes (+8.3%, P<.001) and osteoarthritis (+7.6%, P=.003) and with MIPS-related quality measures, such as diabetes eye examinations (+22%, P<.001), depression screening (+11%, P<.001), and asthma medications (+33%, P<.001). Although the CME availability did not increase enrollment in the study, participants who were offered CME credits were more likely to complete at least 6 of the 8 cases. Conclusions: Although CME availability did not prove to be important, the short, clinically detailed case simulations with real-time feedback and gamified peer benchmarking did lead to significant improvements in evidence-based care decisions among all practicing physicians. Trial Registration: ClinicalTrials.gov NCT03800901; https://clinicaltrials.gov/ct2/show/NCT03800901 
%M 34941547
%R 10.2196/31042
%U https://www.jmir.org/2021/12/e31042
%U https://doi.org/10.2196/31042
%U http://www.ncbi.nlm.nih.gov/pubmed/34941547