Diplomate Spotlight Opening Doors with Board Certification: A Conversation with Long Standing Diplomate Joseph Cook Read Opening Doors with Board Certification: A Conversation with Long Standing Diplomate Joseph Cook
Phoenix Newsletter - July 2025 Available Now: 2026 5-Year Cycle Registration Read Available Now: 2026 5-Year Cycle Registration
Home Research Research Library Physician-Level Continuity of Care and Patient Outcomes in All-Payer Claims Database Physician-Level Continuity of Care and Patient Outcomes in All-Payer Claims Database 2023 Author(s) Dai, Mingliang, Morgan, Zachary J, Russel, Kyle, Bortz, Beth A, Peterson, Lars E, and Bazemore, Andrew W Volume Journal of the American Board of Family Medicine Source Journal of the American Board of Family Medicine Methods: Cross-sectional analysis at patient-level using Virginia All-Payer Claims Database (VA-APCD). Phy-CoC scores were calculated by averaging patient’s Bice-Boxerman Index scores and weighted by the total number of visits. Patient outcomes included total cost and preventable hospitalization. Results: In a sample of 1.6 million Virginians, patients who lived in rural areas or had Medicare as primary insurance were more likely to be attributed to physicians with the highest Phy-CoC scores. Across all adult patient populations, we found that being attributed to physicians with higher Phy-CoC was associated with 7%-11.8% higher total costs, but was not associated with the odds of preventable hospitalization. Results from models with interactions revealed nuanced associations between Phy-CoC and total cost with patient’s age and comorbidity, insurance payer, and the specialty of their physician. Conclusions: In this comprehensive examination of Phy-CoC using all populations from the VAAPCD, we found an overall positive association of higher full panel-based Phy-CoC with total cost, but a non-significant association with the risk of preventable hospitalization. Achieving higher full panelbased Phy-CoC may have unintended cost implications. ( J Am Board Fam Med 2023;36:000–000.) ABFM Research Read all 2025 Reclaiming Medical Professionalism In An Era Of Corporate Healthcare Go to Reclaiming Medical Professionalism In An Era Of Corporate Healthcare 2025 Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence Go to Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence 2025 Validating 8 Area-Based Measures of Social Risk for Predicting Health and Mortality Go to Validating 8 Area-Based Measures of Social Risk for Predicting Health and Mortality 2025 Natural Language Processing Improves Reliable Identification of COVID-19 Compared to Diagnostic Codes Alone Go to Natural Language Processing Improves Reliable Identification of COVID-19 Compared to Diagnostic Codes Alone
Author(s) Dai, Mingliang, Morgan, Zachary J, Russel, Kyle, Bortz, Beth A, Peterson, Lars E, and Bazemore, Andrew W Volume Journal of the American Board of Family Medicine Source Journal of the American Board of Family Medicine
ABFM Research Read all 2025 Reclaiming Medical Professionalism In An Era Of Corporate Healthcare Go to Reclaiming Medical Professionalism In An Era Of Corporate Healthcare 2025 Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence Go to Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence 2025 Validating 8 Area-Based Measures of Social Risk for Predicting Health and Mortality Go to Validating 8 Area-Based Measures of Social Risk for Predicting Health and Mortality 2025 Natural Language Processing Improves Reliable Identification of COVID-19 Compared to Diagnostic Codes Alone Go to Natural Language Processing Improves Reliable Identification of COVID-19 Compared to Diagnostic Codes Alone
2025 Reclaiming Medical Professionalism In An Era Of Corporate Healthcare Go to Reclaiming Medical Professionalism In An Era Of Corporate Healthcare
2025 Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence Go to Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence
2025 Validating 8 Area-Based Measures of Social Risk for Predicting Health and Mortality Go to Validating 8 Area-Based Measures of Social Risk for Predicting Health and Mortality
2025 Natural Language Processing Improves Reliable Identification of COVID-19 Compared to Diagnostic Codes Alone Go to Natural Language Processing Improves Reliable Identification of COVID-19 Compared to Diagnostic Codes Alone