Diplomate Spotlight Opening Doors with Board Certification: A Conversation with Long Standing Diplomate Joseph Cook Read Opening Doors with Board Certification: A Conversation with Long Standing Diplomate Joseph Cook
Phoenix Newsletter - July 2025 Available Now: 2026 5-Year Cycle Registration Read Available Now: 2026 5-Year Cycle Registration
Home Research Research Library Association Between Social Deprivation, Race/Ethnicity, and Unplanned 30-Day Hospital Readmissions for Medicare Beneficiaries Association Between Social Deprivation, Race/Ethnicity, and Unplanned 30-Day Hospital Readmissions for Medicare Beneficiaries 2024 Author(s) Ostrovsky, Andrey, Chen, Weiyun, Zemelman, Cal, Phillips, Robert L, Bazemore, Andrew W, and Winstead, Lauren Keyword(s) Medicare Volume AJMC Source AJMC Social and economic factors impact a person’s health outcomes in addition to traditional clinical factors, and there is growing recognition of the impact of social risk factors on health outcomes. National health insurers like Medicare and Medicaid, which pay for care for people who are the most at risk for experiencing health disparities, need measures of social risk to implement targeted programming and payment allocation to equitably prevent rehospitalizations. Individual social risk variables, such as those collected through social determinants of health (SDOH) surveys, have been used to predict outcomes, but there is growing scrutiny over use of individual variables by insurance carriers because collection of individual data can be deliberately skewed and may be unreliable. Community variables, however, are less gameable and do not suffer from trust barriers to collection while demonstrating compelling associations with meaningful clinical outcomes, like hospital readmission rates. In particular, small geographic area characteristics have been shown to predict 30-day hospital readmission rates across multiple conditions. A measure of neighborhood disadvantage has also been associated with all-cause 30-day hospital readmissions to a particular hospital. The relationship between neighborhood disadvantage and readmissions has been shown to be strongest in the top quartile of social deprivation such that an individual who is poor in a high-disadvantage neighborhood has worse outcomes than an individual who is poor in a medium- or low-disadvantage neighborhood. However, no one to date has shown the relationship between a small area measure of social deprivation and all-cause readmissions at a national scale. Additionally, the role of systemic racism, an important social determinant of health that is not included in social deprivation indices, in all-cause readmissions has not been adequately studied at a national scale. This analysis aimed to use a comprehensive data set of all Medicare hospital discharges across the US over a 1-year period to characterize the relationship between a small-area social deprivation measure, race/ethnicity as a proxy for systemic racism, and all-cause unplanned 30-day readmissions. ABFM Research Read all 2025 Reclaiming Medical Professionalism In An Era Of Corporate Healthcare Go to Reclaiming Medical Professionalism In An Era Of Corporate Healthcare 2025 Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence Go to Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence 2025 Validating 8 Area-Based Measures of Social Risk for Predicting Health and Mortality Go to Validating 8 Area-Based Measures of Social Risk for Predicting Health and Mortality 2025 Natural Language Processing Improves Reliable Identification of COVID-19 Compared to Diagnostic Codes Alone Go to Natural Language Processing Improves Reliable Identification of COVID-19 Compared to Diagnostic Codes Alone
Author(s) Ostrovsky, Andrey, Chen, Weiyun, Zemelman, Cal, Phillips, Robert L, Bazemore, Andrew W, and Winstead, Lauren Keyword(s) Medicare Volume AJMC Source AJMC
ABFM Research Read all 2025 Reclaiming Medical Professionalism In An Era Of Corporate Healthcare Go to Reclaiming Medical Professionalism In An Era Of Corporate Healthcare 2025 Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence Go to Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence 2025 Validating 8 Area-Based Measures of Social Risk for Predicting Health and Mortality Go to Validating 8 Area-Based Measures of Social Risk for Predicting Health and Mortality 2025 Natural Language Processing Improves Reliable Identification of COVID-19 Compared to Diagnostic Codes Alone Go to Natural Language Processing Improves Reliable Identification of COVID-19 Compared to Diagnostic Codes Alone
2025 Reclaiming Medical Professionalism In An Era Of Corporate Healthcare Go to Reclaiming Medical Professionalism In An Era Of Corporate Healthcare
2025 Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence Go to Leveraging Large Language Models to Advance Certification, Physician Learning, and Diagnostic Excellence
2025 Validating 8 Area-Based Measures of Social Risk for Predicting Health and Mortality Go to Validating 8 Area-Based Measures of Social Risk for Predicting Health and Mortality
2025 Natural Language Processing Improves Reliable Identification of COVID-19 Compared to Diagnostic Codes Alone Go to Natural Language Processing Improves Reliable Identification of COVID-19 Compared to Diagnostic Codes Alone