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. ABFM Research Read all 2016 The Diversity of Providers on the Family Medicine Team Go to The Diversity of Providers on the Family Medicine Team 2021 Uniting Public Health and Primary Care for Healthy Communities in the COVID-19 Era and Beyond Go to Uniting Public Health and Primary Care for Healthy Communities in the COVID-19 Era and Beyond 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 2025 Relationships of Educational Debt With Hours Worked and Burnout Symptoms Among Early-Career Family Physicians Go to Relationships of Educational Debt With Hours Worked and Burnout Symptoms Among Early-Career Family Physicians
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 2016 The Diversity of Providers on the Family Medicine Team Go to The Diversity of Providers on the Family Medicine Team 2021 Uniting Public Health and Primary Care for Healthy Communities in the COVID-19 Era and Beyond Go to Uniting Public Health and Primary Care for Healthy Communities in the COVID-19 Era and Beyond 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 2025 Relationships of Educational Debt With Hours Worked and Burnout Symptoms Among Early-Career Family Physicians Go to Relationships of Educational Debt With Hours Worked and Burnout Symptoms Among Early-Career Family Physicians
2016 The Diversity of Providers on the Family Medicine Team Go to The Diversity of Providers on the Family Medicine Team
2021 Uniting Public Health and Primary Care for Healthy Communities in the COVID-19 Era and Beyond Go to Uniting Public Health and Primary Care for Healthy Communities in the COVID-19 Era and Beyond
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
2025 Relationships of Educational Debt With Hours Worked and Burnout Symptoms Among Early-Career Family Physicians Go to Relationships of Educational Debt With Hours Worked and Burnout Symptoms Among Early-Career Family Physicians