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The Impact of Race and Neighborhood Racial Composition on Preventable Readmissions for Diabetic Medicare Home Health Beneficiaries

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Abstract

Background

The recommended home health financial penalty program for preventable readmission does not factor race/ethnicity and neighborhood racial compositions into the determination of preventable readmission rates. Home health agencies may avoid beneficiaries from certain racial/ethnic groups and neighborhoods if these two factors have an effect on preventable readmissions. We examined the association between preventable readmissions with race/ethnicity and neighborhood racial composition.

Methods

Several 2009 national data were used, such as the Master Beneficiary Summary File, Medicare Provider Analysis and Review File, and Outcome Assessment Information Set. Our sample consisted of diabetic Medicare home health beneficiaries (African-Americans and Whites only). We analyzed predictors of time-to-first 30-day preventable readmission, including short/long-term diabetic complications, chronic obstructive pulmonary disease/asthma, bacterial pneumonia, dehydration, urinary tract infection, hypertension, heart failure, angina without procedure, uncontrolled diabetes, and lower-extremity amputation.

Results

There were 86,567, 17,262, and 11,392 observations in neighborhoods with low (6 % African-Americans), moderate (35 % African-Americans), and high (76 % African-Americans) density of African-Americans, respectively. Using Cox regression models, we found that in neighborhoods with moderate and high density of African-Americans, African-Americans had 21 % (hazard ratio (HR) 1.21; 95 % confidence interval (CI) 1.04–1.39) and 24 % (HR 1.24; 95 % CI 1.01–1.52) significantly higher hazards of 30-day preventable readmissions than Whites, respectively.

Conclusion

Race and neighborhood racial compositions are beyond home health providers’ control. These two factors should be considered as covariates for the preventable readmissions in the recommended home health financial penalty program.

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Acknowledgments

The manuscript was accepted when the corresponding author was affiliated with UNTHSC but was published after the corresponding author joined UAMS.

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Author notes

  1. Hsueh-Fen Chen

    Present address: Department of Health Policy and Management College of Public Health, University of Arkansas Medical Sciences, 4301 West Markam, Slot 820-12, Little Rock, AR, USA

Authors and Affiliations

  1. University of North Texas Health Science Center, Fort Worth, TX, USA

    Hsueh-Fen Chen

  2. Sinai Urban Health Institute, 1500 South Fairfield Avenue, Kurtzon 437, Chicago, IL, 60608, USA

    Sharon Homan

  3. Department of Health Management and Policy School of Public Health, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX, 76107, USA

    Erin Carlson

  4. Department of Health Policy and Management, University of Kansas Medical Center, 3901 Rainbow Blvd, Kansas City, KS, 66160, USA

    Taiye Popoola

  5. Shool of Nursing, University of Texas- Austin, 1710 Red River Street, Austin, TX, 78701, USA

    Kavita Radhakrishnan

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Correspondence to Hsueh-Fen Chen.

Ethics declarations

The study was approved by the IRB at the University of North Texas Health Science Center. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standard.

Funding

This study was supported by the Junior Faculty Seed Fund at the University of North Texas Health Science Center (UNTHSC). The views expressed in this publication are the views of the authors and do not necessarily reflect the views of the UNTHSC.

Conflict of Interest

The authors declare that they have no conflicts of interest.

Informed Consent

This study was based on the secondary data from the Medicare claim and assessment files and several national data at the organization and community levels. The authors were not able to use these secondary data to identify individual personal information. Thus obtaining the consent from individual person was not feasible; however, the authors followed the rules under the CMS data user agreement.

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Chen, HF., Homan, S., Carlson, E. et al. The Impact of Race and Neighborhood Racial Composition on Preventable Readmissions for Diabetic Medicare Home Health Beneficiaries. J. Racial and Ethnic Health Disparities 4, 648–658 (2017). https://doi.org/10.1007/s40615-016-0268-2

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  • DOI: https://doi.org/10.1007/s40615-016-0268-2

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