research Performance Evaluation of the Generative Pre-trained Transformer (GPT-4) on the Family Medicine In-Training Examination Read Performance Evaluation of the Generative Pre-trained Transformer (GPT-4) on the Family Medicine In-Training Examination
Phoenix Newsletter - March 2025 President’s Message: ABFM’s Unwavering Commitment to Diplomates and the Specialty Read President’s Message: ABFM’s Unwavering Commitment to Diplomates and the Specialty
A Conversation with Dr. Phillip Wagner “Family Medicine Was All I Ever Wanted to Do” Dr. Phillip Wagner Read “Family Medicine Was All I Ever Wanted to Do”
Home Research Research Library Family Medicine Residency Graduates’ Preparation for Quality Improvement Leadership Family Medicine Residency Graduates’ Preparation for Quality Improvement Leadership 2019 Author(s) Lichkus, Jonathan, Fang, Bo, and Peterson, Lars E Topic(s) Education & Training, and Achieving Health System Goals Keyword(s) Graduate Medical Education, and Visiting Scholar/Fellow Volume Journal of Graduate Medical Education Source Journal of Graduate Medical Education Background: Training in quality improvement (QI) is a standard component of family medicine residency education. Graduating family medicine residents’ ability to lead QI initiatives is unknown. Objective: We assessed the preparedness of graduating family medicine residents to lead QI projects and to identify factors that may increase such readiness. Methods: Milestone data for all graduating family medicine residents were linked to a practice demographic questionnaire completed by the same residents who registered for the American Board of Family Medicine certification examination between 2014 and 2017. The change in self-assessed QI preparedness over time and its association with faculty-assigned milestone ratings were examined using descriptive and regression analyses. Results: The questionnaire had a 100% response rate (12 208 responded). Between 2014 and 2017, the percentage of residents who self-reported being “extremely” or “moderately” prepared to lead QI projects increased from 72.7% (2208 of 3038) to 75.8% (2434 of 3210, P = .009). Self-reported QI team leadership was associated with 93% higher odds of feeling extremely prepared compared to moderately prepared (odds ratio 1.93, 95% CI 1.58-2.35). The average midyear faculty-assigned milestone rating for QI among residents who felt “extremely” prepared was 3.28 compared to 3.14 among those who felt “not at all” prepared. Conclusions: Over the past 4 years, family medicine residents’ self-assessed preparedness to lead QI projects has barely increased. There was no correlation between self-assessed preparation and faculty-assigned milestone rating. However, we found a small association between self-reported QI leadership and self-assessed QI preparedness. Read More ABFM Research Read all 2022 Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health Go to Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health 2018 Primary Care Practices’ Abilities And Challenges In Using Electronic Health Record Data For Quality Improvement Go to Primary Care Practices’ Abilities And Challenges In Using Electronic Health Record Data For Quality Improvement 2019 The Current State of Research Capacity in US Family Medicine Departments Go to The Current State of Research Capacity in US Family Medicine Departments 2015 Do family physicians electronic health records support meaningful use? Go to Do family physicians electronic health records support meaningful use?
Author(s) Lichkus, Jonathan, Fang, Bo, and Peterson, Lars E Topic(s) Education & Training, and Achieving Health System Goals Keyword(s) Graduate Medical Education, and Visiting Scholar/Fellow Volume Journal of Graduate Medical Education Source Journal of Graduate Medical Education
ABFM Research Read all 2022 Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health Go to Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health 2018 Primary Care Practices’ Abilities And Challenges In Using Electronic Health Record Data For Quality Improvement Go to Primary Care Practices’ Abilities And Challenges In Using Electronic Health Record Data For Quality Improvement 2019 The Current State of Research Capacity in US Family Medicine Departments Go to The Current State of Research Capacity in US Family Medicine Departments 2015 Do family physicians electronic health records support meaningful use? Go to Do family physicians electronic health records support meaningful use?
2022 Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health Go to Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health
2018 Primary Care Practices’ Abilities And Challenges In Using Electronic Health Record Data For Quality Improvement Go to Primary Care Practices’ Abilities And Challenges In Using Electronic Health Record Data For Quality Improvement
2019 The Current State of Research Capacity in US Family Medicine Departments Go to The Current State of Research Capacity in US Family Medicine Departments
2015 Do family physicians electronic health records support meaningful use? Go to Do family physicians electronic health records support meaningful use?
