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 Quality of Care for Latinx Children with Asthma: Associations with Language Concordance and Continuity of Care Quality of Care for Latinx Children with Asthma: Associations with Language Concordance and Continuity of Care 2023 Author(s) Hodes, Tahlia, Marino, Miguel, Lucas, Jennifer A, Bazemore, Andrew W, Peterson, Lars E, Trivedi, Michelle K, Giebultowicz, Sophia, and Heintzman, John D Volume Journal of the American Board of Family Medicine Source Journal of the American Board of Family Medicine Methods: We utilized an electronic health record dataset from a multistate network of community health centers to compare influenza vaccinations and inhaled steroid prescriptions, by ethnicity and language concordance groups overall and stratified by COC. Results: We analyzed electronic health records for children with asthma (n = 38,442) age 3 to 17 years with ≥2 office visits between 2005 to 2017. Overall, 64% of children had low COC (defined as COC < 0.5) while 21% had high COC (defined as >0.75). All Latinx children had higher rates and odds of receiving influenza vaccination compared with non-Hispanic White children. In addition, Spanishpreferring Latinx children had higher rates and odds of being prescribed inhaled steroids while English-preferring Latinx children had lower odds (OR = 0.85 95%CI = 0.73,0.98) compared with nonHispanic White children. Conclusion: Overall, Latinx children regardless of COC category or language concordance were more likely to receive the influenza vaccine. English-preferring Latinx children with persistent asthma received fewer inhaled steroid prescriptions compared with non-Hispanic White children. Panel chart review and seeing a practice partner might be one way to combat these inequities. ( J Am Board Fam Med 2023;36:616–625.) 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) Hodes, Tahlia, Marino, Miguel, Lucas, Jennifer A, Bazemore, Andrew W, Peterson, Lars E, Trivedi, Michelle K, Giebultowicz, Sophia, and Heintzman, John D Volume Journal of the American Board of Family Medicine Source Journal of the American Board of Family Medicine
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