ObjectiveTo quantify racial, ethnic, and income‐based disparities in home health (HH) patients' functional improvement within and between HH agencies (HHAs).Data Sources2016–2017 Outcome and Assessment Information Set, Medicare Beneficiary Summary File, and Census data.Data Collection/Extraction MethodsNot Applicable.Study DesignWe use multinomial‐logit analyses with and without HHA fixed effects. The outcome is a mutually exclusive five‐category outcome: (1) any functional improvement, (2) no functional improvement, (3) death while a patient, (4) transfer to an inpatient setting, and (5) continuing HH as of December 31, 2017. The adjusted outcome rates are calculated by race, ethnicity, and income level using predictive margins.Principal FindingsOf the 3+ million Medicare beneficiaries with a HH start‐of‐care assessment in 2016, 77% experienced functional improvement at discharge, 8% were discharged without functional improvement, 0.6% died, 2% were transferred to an inpatient setting, and 12% continued using HH. Adjusting for individual‐level characteristics, Black, Hispanic, American Indian/Alaska Native (AIAN), and low‐income HH patients were all more likely to be discharged without functional improvement (1.3 pp [95% CI: 1.1, 1.5], 1.5 pp [95% CI: 0.8, 2.1], 1.2 pp [95% CI: 0.6, 1.8], 0.7 pp [95% CI:0.5, 0.8], respectively) compared to White and higher income patients. After including HHA fixed effects, the differences for Black, Hispanic, and AIAN HH patients were mitigated. However, income‐based disparities persisted within HHAs. Black‐White, Hispanic‐White, and AIAN‐White disparities were largely driven by between‐HHA differences, whereas income‐based disparities were mostly due to within‐HHA differences, and Asian American/Pacific Islander patients did not experience any observable disparities.ConclusionsBoth within‐ and between‐HHA differences contribute to the overall disparities in functional improvement. Mitigating functional improvement inequities will require a diverse set of culturally appropriate and socially conscious interventions. Improving the quality of HHAs that serve more marginalized patients and incentivizing improved equity within HHAs are approaches that are imperative for ameliorating outcomes.
Background: Errors in racial and ethnic classification of Medicare beneficiaries limit health services research on minority health and health disparities among priority populations, including American Indians and Alaskan Natives.Objective: To compare the agreement and accuracy of three sources of race and ethnicity information contained in the Medicare data warehouse: 1) the Enrollment Database (EDB) which originate from Social Security data; 2) the Research Triangle Institute (RTI) imputed data based on name and geography; and 3) self-reported race and ethnicity data collected during routine home health care assessments as part of the Outcome and Assessment Information Set (OASIS).Subjects: Medicare beneficiaries over the age of 18 who received home health care in 2015 (N = 4,243,090). Measures: Percent agreement, sensitivity, specificity, positive predictive value, and Cohen’s kappa coefficient. Results: Compared to self-reported race/ethnicity data from OASIS, the RTI race code is more accurate than the EDB race code. Non-Hispanic whites and blacks were correctly classified by the RTI race code with 97% accuracy. However, more than half of American Indians/Alaskan Natives, one-fourth of Asian American/Pacific Islanders, and nearly one-tenth of Hispanics were misclassified by the RTI race code. Misclassification of race/ethnicity occurred less often for men, compared to women. Discussion: These findings highlight the strengths and limitations of using race/ethnicity classifications contained in Medicare administrative data. Health services and policy researchers should consider using self-identified race/ethnicity information to augment administrative datasources. This is especially important for research that aims to include Asian Americans/Pacific Islanders and American Indians/Alaskan Natives.
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