Tuesday, April 29, 2025
4/29/2025
Prediction of Practice Change in Primary Care Following Guideline Updates - PROJECT SUMMARY The central idea of evidence-based medicine is that clinical decisions should be made on the basis of the best available research. Few practicing clinicians can stay current with the vast quantity of clinical research relevant to their patients, though. This is especially true for primary care providers, who care for patients with a broad range of conditions. Treatment guidelines are therefore an essential mechanism for disseminating research and promoting high-quality clinical care among physicians who cannot directly engage with published clinical research. Still, the time to widespread guideline implementation is too long. Delaying the uptake of guidelines has been associated with worse patient outcomes, particularly among patients from marginalized groups. Using the American Family Cohort, the nation’s largest clinical repository of electronic health records from primary care, we will analyze the response to four guideline updates that have different barriers to implementation: expansion of screening for Hepatitis C virus; vaccination of older adults against pneumococcus with newly approved vaccines; provision of preexposure prophylaxis (PrEP) for Human Immunodeficiency Virus; and initiation of screening for colorectal cancer at age 45 among people of average risk. Our analyses will support the dissemination of guidelines into primary care in two distinct ways. First, we will assess the predictors of time to practice change in the direction of more guideline- concordant care for each of the four guideline update case studies, as determined by change-point analysis. We will use a multi-level model to then predict time to practice change, integrating patient, provider, and practice site characteristics. This will allow guideline developers to forecast the uptake and potential impact – including impact on disparities – of potential guideline updates. Next, we will develop phenotypes of clinicians based on their response to guideline updates by using latent class analysis to identify distinctive patterns of practice change across the combination of all four guideline updates. This latent class analysis will show how enabling factors and barriers to implementation can interact to generate predictable patterns of guideline response. In sum, our second aim will support market segmentation and the individualization of educational outreach that can improve the efficiency and impact of dissemination activities.
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