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Home Research Research Library Variation in Practice Patterns of Early- and Later- Career Family Physicians Variation in Practice Patterns of Early- and Later- Career Family Physicians 2023 Author(s) Carek, Peter J, Cheng, Yue, Bazemore, Andrew W, and Peterson, Lars E Keyword(s) Visiting Scholar/Fellow Volume Journal of the American Board of Family Medicine Source Journal of the American Board of Family Medicine Methods: Data on early career FPs came from the American Board of Family Medicine’s National Graduate Survey (NGS) and on later career FPs from its Continuous Certification Questionnaire (CCQ). Both cohorts could complete the Practice Demographic Survey (PDS) 3 years later. Longitudinal cohorts were from 2016 to 2019 and 2017 to 2020, respectively. All surveys included identical items on scope of practice, practice type, organization, and location. We characterized physicians as outpatient continuity only, outpatient and inpatient care (mixed practice), and no outpatient continuity (for example, hospitalist). We conducted repeated cross-sectional and longitudinal analysis of practice type. Results: Our sample included 8,492 NGS and 30,491 CCQ FPs. In both groups, the vast majority provided outpatient continuity of care (77% to 81%). Approximately 25% of NGS had a mixed practice compared with approximately 16% of the CCQ group. The percent of FPs who had a mixed practice declined in both groups (34.21% to 27.10% and 23.88% to 19.33%). In both groups, physicians with higher odds of leaving mixed practice were in metropolitan counties or changed practice types. Conclusion: Although early-career FPs more frequently reported providing both inpatient and outpatient care and serving as hospitalists compared with later-career FPs, both groups had a decline in frequency of providing mixed practice. This change after only 3 years in practice has significant implications for patient care and medical education. ( J Am Board Fam Med 2023;00:000–000.) 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) Carek, Peter J, Cheng, Yue, Bazemore, Andrew W, and Peterson, Lars E Keyword(s) Visiting Scholar/Fellow 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