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 Factors influencing family physician adoption of electronic health records (EHRs) Factors influencing family physician adoption of electronic health records (EHRs) 2013 Topic(s) Role of Primary Care Keyword(s) Health Information Technology (HIT) Volume Journal of the American Board of Family Medicine Source Journal of the American Board of Family Medicine BACKGROUND: Physician and practice characteristics associated with family physician adoption of electronic health records (EHRs) remain largely unexplored but may be important for tailoring policies and interventions. METHODS: This was a cross-sectional study of EHR adoption using American Board of Family Medicine certification census data (2006-2011) for over 41,000 family physicians to test associations between demographic, geographic, and practice characteristics and EHR adoption. RESULTS: EHR adoption rates for family physicians grew from 37% in 2006 to 68% in 2011. No significant association was found with rural status (odds ration [OR], 0.985; 95% confidence interval [CI], 0.932-1.042). Practicing in a medically underserved location (OR, 0.868; 95% CI, 0.822-0.917) or geographic health professional shortage areas (OR, 0.904; 95% CI, 0.831-0.984), or being an international medical graduate (OR, 0.769; 95% CI, 0.748-0.846) were negatively associated with adoption. Compared with physicians in group practices, physicians in solo practices (OR, 0.465; 95% CI, 0.439-0.493) and small practices (OR, 0.769; 95% CI, 0.720-0.820) were less likely to adopt EHRs, whereas those in health maintenance organizations (OR, 5.482; 95% CI, 4.657-6.454) or with faculty status (OR, 1.527; 95% CI, 1.386-1.684) were more likely. CONCLUSIONS: Variation in EHR adoption is associated with physician and practice characteristics that may help guide intervention. These findings may be important to other specialties and could instruct interventions to improve adoption. Certification boards could play an important role in tracking EHR adoption and help target resources and facilitation. Read More ABFM Research Read all 2014 Methods for Performing Survival Curve Quality-of-Life Assessments Go to Methods for Performing Survival Curve Quality-of-Life Assessments 2020 Shaping Keystones in a Time of Transformation: ABFM’s Efforts to Advance Leadership & Scholarship in Family Medicine Go to Shaping Keystones in a Time of Transformation: ABFM’s Efforts to Advance Leadership & Scholarship in Family Medicine 2024 Small Independent Primary Care Practices Serving Socially Vulnerable Urban Populations Go to Small Independent Primary Care Practices Serving Socially Vulnerable Urban Populations 2022 Implementing High-Quality Primary Care: To What End? Go to Implementing High-Quality Primary Care: To What End?
Topic(s) Role of Primary Care Keyword(s) Health Information Technology (HIT) Volume Journal of the American Board of Family Medicine Source Journal of the American Board of Family Medicine
ABFM Research Read all 2014 Methods for Performing Survival Curve Quality-of-Life Assessments Go to Methods for Performing Survival Curve Quality-of-Life Assessments 2020 Shaping Keystones in a Time of Transformation: ABFM’s Efforts to Advance Leadership & Scholarship in Family Medicine Go to Shaping Keystones in a Time of Transformation: ABFM’s Efforts to Advance Leadership & Scholarship in Family Medicine 2024 Small Independent Primary Care Practices Serving Socially Vulnerable Urban Populations Go to Small Independent Primary Care Practices Serving Socially Vulnerable Urban Populations 2022 Implementing High-Quality Primary Care: To What End? Go to Implementing High-Quality Primary Care: To What End?
2014 Methods for Performing Survival Curve Quality-of-Life Assessments Go to Methods for Performing Survival Curve Quality-of-Life Assessments
2020 Shaping Keystones in a Time of Transformation: ABFM’s Efforts to Advance Leadership & Scholarship in Family Medicine Go to Shaping Keystones in a Time of Transformation: ABFM’s Efforts to Advance Leadership & Scholarship in Family Medicine
2024 Small Independent Primary Care Practices Serving Socially Vulnerable Urban Populations Go to Small Independent Primary Care Practices Serving Socially Vulnerable Urban Populations
2022 Implementing High-Quality Primary Care: To What End? Go to Implementing High-Quality Primary Care: To What End?