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
Beyond the Clinic Family Medicine on a Mission Part 1: How Air Force Physicians Achieve Humanitarian Goals Read Family Medicine on a Mission Part 1: How Air Force Physicians Achieve Humanitarian Goals
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
Home Research Research Library ABFM to Simplify Maintenance of Certification (MOC) for Family Physicians and Make It More Meaningful: A Family Medicine Registry ABFM to Simplify Maintenance of Certification (MOC) for Family Physicians and Make It More Meaningful: A Family Medicine Registry 2015 Author(s) Phillips, Robert L Topic(s) Family Medicine Certification, Role of Primary Care, and Achieving Health System Goals Keyword(s) Health Information Technology (HIT), Measurement, and Physician Experience (Burnout / Satisfaction) Volume Journal of the American Board of Family Medicine Source Journal of the American Board of Family Medicine The American Board of Family Medicine (ABFM) launches the start of a family medicine registry with a study called the Trial of Aggregate Data Exchange for Maintenance of Certification and Raising Quality (TRADEMaRQ). This study is supported by the US Agency for Healthcare Research and Quality and is the first phase of a nearly $7 million investment by the ABFM to make maintenance of certification (MOC) easier and more meaningful, to help physicians turn their electronic health record (EHR) data into useful information, and to support the Physician Quality Reporting System (PQRS), meaningful use, and other reporting needs. The ABFM is the first board to sponsor a registry, and this is the first clinical registry to support MOC. Read More ABFM Research Read all 2012 Cheating: its implications for American Board of Family Medicine examinees Go to Cheating: its implications for American Board of Family Medicine examinees 2019 Debt and the emerging physician workforce: the relationship between educational debt and family medicine residents’ practice and fellowship intentions Go to Debt and the emerging physician workforce: the relationship between educational debt and family medicine residents’ practice and fellowship intentions 2024 What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care Go to What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care 1995 Educational resource sharing and collaborative training in family practice and internal medicine. A statement from the American Boards of Internal Medicine and Family Practice Go to Educational resource sharing and collaborative training in family practice and internal medicine. A statement from the American Boards of Internal Medicine and Family Practice
Author(s) Phillips, Robert L Topic(s) Family Medicine Certification, Role of Primary Care, and Achieving Health System Goals Keyword(s) Health Information Technology (HIT), Measurement, and Physician Experience (Burnout / Satisfaction) Volume Journal of the American Board of Family Medicine Source Journal of the American Board of Family Medicine
ABFM Research Read all 2012 Cheating: its implications for American Board of Family Medicine examinees Go to Cheating: its implications for American Board of Family Medicine examinees 2019 Debt and the emerging physician workforce: the relationship between educational debt and family medicine residents’ practice and fellowship intentions Go to Debt and the emerging physician workforce: the relationship between educational debt and family medicine residents’ practice and fellowship intentions 2024 What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care Go to What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care 1995 Educational resource sharing and collaborative training in family practice and internal medicine. A statement from the American Boards of Internal Medicine and Family Practice Go to Educational resource sharing and collaborative training in family practice and internal medicine. A statement from the American Boards of Internal Medicine and Family Practice
2012 Cheating: its implications for American Board of Family Medicine examinees Go to Cheating: its implications for American Board of Family Medicine examinees
2019 Debt and the emerging physician workforce: the relationship between educational debt and family medicine residents’ practice and fellowship intentions Go to Debt and the emerging physician workforce: the relationship between educational debt and family medicine residents’ practice and fellowship intentions
2024 What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care Go to What Complexity Science Predicts About the Potential of Artificial Intelligence/Machine Learning to Improve Primary Care
1995 Educational resource sharing and collaborative training in family practice and internal medicine. A statement from the American Boards of Internal Medicine and Family Practice Go to Educational resource sharing and collaborative training in family practice and internal medicine. A statement from the American Boards of Internal Medicine and Family Practice
