Home Research Research Library Maternity Care Tracks at US Family Medicine Residency Programs Maternity Care Tracks at US Family Medicine Residency Programs 2021 Author(s) Roskos, Steven E, Barreto, Tyler W, Phillips, Julie P, King, Valerie J, Eidson-Ton, W Suzanne, and Eden, Aimee R Topic(s) Education & Training, and What Family Physicians Do Keyword(s) Graduate Medical Education, and Maternity Care Volume Family Medicine Source Family Medicine BACKGROUND AND OBJECTIVES: The number of family physicians providing maternity care continues to decline, jeopardizing access to needed care for underserved populations. Accreditation changes in 2014 provided an opportunity to create family medicine residency maternity care tracks, providing comprehensive maternity care training only for interested residents. We examined the relationship between maternity care tracks and residents’ educational experiences and postgraduate practice. METHODS: We included questions on maternity care tracks in an omnibus survey of family medicine residency program directors (PDs). We divided respondent programs into three categories: “Track,” “No Track Needed,” and “No Track.” We compared these program types by their characteristics, number of resident deliveries, and number of graduates practicing maternity care. RESULTS: The survey response rate was 40%. Of the responding PDs, 79 (32%) represented Track programs, 55 (22%) No Track Needed programs, and 94 (38%) No Track programs. Residents in a track attended more deliveries than those not in a track (at Track programs) and those at No Track Needed and No Track programs. No Track Needed programs reported the highest proportion of graduates accepting positions providing inpatient maternity care in 2019 (21%), followed by Track programs (17%) and No Track programs (5%; P<.001). CONCLUSIONS: Where universal robust maternity care education is not feasible, maternity care tracks are an excellent alternative to provide maternity care training and produce graduates who will practice maternity care. Programs that cannot offer adequate experience to achieve competence in inpatient maternity care may consider instituting a maternity care track. ABFM Research Read all 2021 Is Artificial Intelligence the Key to Reclaiming Relationships in Primary Care? Go to Is Artificial Intelligence the Key to Reclaiming Relationships in Primary Care? 2024 Setting the Target: Comparing Family Medicine Among US Allopathic Target Schools Go to Setting the Target: Comparing Family Medicine Among US Allopathic Target Schools 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 1990 American Board of Family Practice statistics Go to American Board of Family Practice statistics
Author(s) Roskos, Steven E, Barreto, Tyler W, Phillips, Julie P, King, Valerie J, Eidson-Ton, W Suzanne, and Eden, Aimee R Topic(s) Education & Training, and What Family Physicians Do Keyword(s) Graduate Medical Education, and Maternity Care Volume Family Medicine Source Family Medicine
ABFM Research Read all 2021 Is Artificial Intelligence the Key to Reclaiming Relationships in Primary Care? Go to Is Artificial Intelligence the Key to Reclaiming Relationships in Primary Care? 2024 Setting the Target: Comparing Family Medicine Among US Allopathic Target Schools Go to Setting the Target: Comparing Family Medicine Among US Allopathic Target Schools 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 1990 American Board of Family Practice statistics Go to American Board of Family Practice statistics
2021 Is Artificial Intelligence the Key to Reclaiming Relationships in Primary Care? Go to Is Artificial Intelligence the Key to Reclaiming Relationships in Primary Care?
2024 Setting the Target: Comparing Family Medicine Among US Allopathic Target Schools Go to Setting the Target: Comparing Family Medicine Among US Allopathic Target Schools
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