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
Diplomate Spotlight “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 Interoperability among hospitals treating populations that have been marginalized Interoperability among hospitals treating populations that have been marginalized 2023 Author(s) Everson, Jordan, Patel, Vaishali, Bazemore, Andrew W, and Phillips, Robert L Topic(s) Role of Primary Care, and Achieving Health System Goals Keyword(s) Health Information Technology (HIT) Volume Health Services Research Source Health Services Research Objective To test whether differences in hospital interoperability are related to the extent to which hospitals treat groups that have been economically and socially marginalized. Data Sources and Study Setting Data on 2393 non-federal acute care hospitals in the United States from the American Hospital Association Information Technology Supplement fielded in 2021, the 2019 Medicare Cost Report, and the 2019 Social Deprivation Index. Study Design Cross-sectional analysis. Data Collection/Extraction Methods We identified five proxy measures related to marginalization and assessed the relationship between those measures and the likelihood that hospitals engaged in all four domains of interoperable information exchange and participated in national interoperability networks in cross-sectional analysis. Principal Findings In unadjusted analysis, hospitals that treated patients from zip codes with high social deprivation were 33% less likely to engage in interoperable exchange (Relative Risk = 0.67, 95% CI: 0.58–0.76) and 24% less likely to participate in a national network than all other hospitals (RR = 0.76; 95% CI: 0.66–0.87). Critical Access Hospitals (CAH) were 24 percent less likely to engage in interoperable exchange (RR = 0.76; 95% CI: 0.69–0.83) but not less likely to participate in a national network (RR = 0.97; 95% CI: 0.88–1.06). No difference was detected for 2 measures (high Disproportionate Share Hospital percentage and Medicaid case mix) while 1 was associated with a greater likelihood to engage (high uncompensated care burden). The association between social deprivation and interoperable exchange persisted in an analysis examining metropolitan and rural areas separately and in adjusted analyses accounting for hospital characteristics. Conclusions Hospitals that treat patients from areas with high social deprivation were less likely to engage in interoperable exchange than other hospitals, but other measures were not associated with lower interoperability. The use of area deprivation data may be important to monitor and address hospital clinical data interoperability disparities to avoid related health care disparities. Read More ABFM Research Read all 2020 Using Machine Learning to Predict Primary Care and Advance Workforce Research Go to Using Machine Learning to Predict Primary Care and Advance Workforce Research 2019 PURSUING PRACTICAL PROFESSIONALISM: FORM FOLLOWS FUNCTION Go to PURSUING PRACTICAL PROFESSIONALISM: FORM FOLLOWS FUNCTION 2019 Experience of Family Physicians in Practice Transformation Networks Go to Experience of Family Physicians in Practice Transformation Networks 2015 Envisioning a New Health Care System for America Go to Envisioning a New Health Care System for America
Author(s) Everson, Jordan, Patel, Vaishali, Bazemore, Andrew W, and Phillips, Robert L Topic(s) Role of Primary Care, and Achieving Health System Goals Keyword(s) Health Information Technology (HIT) Volume Health Services Research Source Health Services Research
ABFM Research Read all 2020 Using Machine Learning to Predict Primary Care and Advance Workforce Research Go to Using Machine Learning to Predict Primary Care and Advance Workforce Research 2019 PURSUING PRACTICAL PROFESSIONALISM: FORM FOLLOWS FUNCTION Go to PURSUING PRACTICAL PROFESSIONALISM: FORM FOLLOWS FUNCTION 2019 Experience of Family Physicians in Practice Transformation Networks Go to Experience of Family Physicians in Practice Transformation Networks 2015 Envisioning a New Health Care System for America Go to Envisioning a New Health Care System for America
2020 Using Machine Learning to Predict Primary Care and Advance Workforce Research Go to Using Machine Learning to Predict Primary Care and Advance Workforce Research
2019 PURSUING PRACTICAL PROFESSIONALISM: FORM FOLLOWS FUNCTION Go to PURSUING PRACTICAL PROFESSIONALISM: FORM FOLLOWS FUNCTION
2019 Experience of Family Physicians in Practice Transformation Networks Go to Experience of Family Physicians in Practice Transformation Networks
2015 Envisioning a New Health Care System for America Go to Envisioning a New Health Care System for America
