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Clinical Appropriateness Measures Collaborative Project

Research

A Data-Drive Collaboration to Promote Evidence-Based Care

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Published on Dec 15, 2021

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Background

In 2020-2021, ÐÜèÊÓƵlaunched a project with Dr. Martin Makary, a professor at the Johns Hopkins University School of Medicine, on a data-driven, collaborative approach to promote evidence-based care. The project is based on an implementation science methodology published by Dr. Makary’s team in several academic peer-reviewed journals. In this research, the team analyzed data from the Centers for Medicare & Medicaid Services (CMS) and commercial payers using physician-led appropriateness measures based on consensus among specialists. Physicians were then benchmarked to their peers, and data was shared at an individual physician level. Results from the intervention showed 85% of physicians practicing outside of the standard changed behavior to meet consensus practice standards.

Using this same data-driven model, several ÐÜèÊÓƵmember health insurance providers collaborated with Dr. Makary’s team in a similar project to increase adherence with evidence-based care, improve patient care, and reduce unnecessary care across different medical specialties. The participating health insurance providers provided their claims analysis based on the metrics and methodology provided by the Johns Hopkins study team.