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Home Research Research Library An Intersectional Analysis of Social Deprivation and Patient Characteristics on Nirmatrelvir-Ritonavir for Treatment of COVID-19 in U.S. Primary Care Practices, 2021 to 2023 An Intersectional Analysis of Social Deprivation and Patient Characteristics on Nirmatrelvir-Ritonavir for Treatment of COVID-19 in U.S. Primary Care Practices, 2021 to 2023 2025 Author(s) Velásquez, Esther E, Kamdar, Neil S, Hendrix, Nathaniel, Wang, Xiaoyu, Phillips, Robert L, and Rehkopf, David H Topic(s) Achieving Health System Goals Keyword(s) Population Health Volume Journal of Primary Care & Community Health Source Journal of Primary Care & Community Health Objective:Calculate rates of nirmatrelvir-ritonavir prescription and assess area-level social deprivation as an effect modifier of patient characteristics on nirmatrelvir-ritonavir for the treatment of COVID-19.Methods:Retrospective cohort study December 22, 2021 to June 30, 2023 using electronic health record (EHR) data of primary care patients from the American Family Cohort (AFC). Eligible patients had documented COVID-19 between December 15, 2021 and February 28, 2023; ≥1 healthcare encounter between January 1, 2020 and December 14, 2021; and ≥1 healthcare encounter between December 15, 2021 and June 30, 2023. Of the 3 678 474 AFC patients observed during the study period, 86 043 met inclusion criteria. Social deprivation was measured by census tract of patient residence using 2020 Social Deprivation Index (SDI) values; quintiles were calculated using national census tract distribution with lower values indicating less deprivation. The primary statistical analysis estimated the probability of nirmatrelvir-ritonavir prescription using logistic regression. The secondary analysis assessed area-level social deprivation as an effect modifier of patient characteristics on nirmatrelvir-ritonavir prescribing.Results:Of the cohort, 26 797 (31.1%) patients were prescribed nirmatrelvir-ritonavir. Asian patients were more likely than White patients to receive a nirmatrelvir-ritonavir prescription in the lowest 2 quintiles of social deprivation (Q1: OR = 1.33 (95% CI = 1.10, 1.59); Q2: OR = 1.29 (95% CI = 1.02, 1.61)). Non-Hispanic/Latino patients in the lowest quintile had 1.32 times the odds of nirmatrelvir-ritonavir prescribing (95% CI = 1.12, 1.56) compared to Hispanic/Latino patients; however, in the third, fourth, and fifth quintiles, non-Hispanic/Latino patients had a reduced odds of a nirmatrelvir-ritonavir prescription compared to Hispanic/Latino patients (Q3: OR = 0.83 (95% CI = 0.73, 0.95); Q4: OR = 0.67 (95% CI = 0.60, 0.75); Q5: OR = 0.67 (95% CI = 0.56, 0.80)).Conclusions:Our research suggests intersectionality between patient race/ethnicity with economic status – with meaningful implications for understanding access to new medications within primary care, as they relate to treatment for communicable diseases. ABFM Research Read all 2024 Electronic Health Record Usability, Satisfaction, and Burnout for Family Physicians Go to Electronic Health Record Usability, Satisfaction, and Burnout for Family Physicians 2018 Physician Perceptions of Performance Feedback in a Quality Improvement Activity Go to Physician Perceptions of Performance Feedback in a Quality Improvement Activity 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 2014 Methods for Performing Survival Curve Quality-of-Life Assessments Go to Methods for Performing Survival Curve Quality-of-Life Assessments
Author(s) Velásquez, Esther E, Kamdar, Neil S, Hendrix, Nathaniel, Wang, Xiaoyu, Phillips, Robert L, and Rehkopf, David H Topic(s) Achieving Health System Goals Keyword(s) Population Health Volume Journal of Primary Care & Community Health Source Journal of Primary Care & Community Health
ABFM Research Read all 2024 Electronic Health Record Usability, Satisfaction, and Burnout for Family Physicians Go to Electronic Health Record Usability, Satisfaction, and Burnout for Family Physicians 2018 Physician Perceptions of Performance Feedback in a Quality Improvement Activity Go to Physician Perceptions of Performance Feedback in a Quality Improvement Activity 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 2014 Methods for Performing Survival Curve Quality-of-Life Assessments Go to Methods for Performing Survival Curve Quality-of-Life Assessments
2024 Electronic Health Record Usability, Satisfaction, and Burnout for Family Physicians Go to Electronic Health Record Usability, Satisfaction, and Burnout for Family Physicians
2018 Physician Perceptions of Performance Feedback in a Quality Improvement Activity Go to Physician Perceptions of Performance Feedback in a Quality Improvement Activity
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
2014 Methods for Performing Survival Curve Quality-of-Life Assessments Go to Methods for Performing Survival Curve Quality-of-Life Assessments