Abstract
Statistical methods for provider profiling are designed to measure healthcare quality and create incentives for low-quality providers to improve. While most existing healthcare quality metrics assess the overall treatment delivered to providers’ entire patient populations, widespread racial and sociodemographic disparities in health outcomes highlight the need to evaluate providers’ healthcare quality across patient subgroups. Disparity measure development at the healthcare provider level is a nascent research area, and existing measures have lacked the statistical rigor and clear definitions of performance benchmarks that are characteristic of traditional provider profiling methodology. In response to these gaps, we propose a formal disparity model for provider evaluations, which can be used to construct null hypotheses and test statistics for concepts such as systemic disparities, equality in performance, and equity in performance. For each of these topics, we define the appropriate performance benchmark in terms of statistical parameters, and describe its relationship with the existing literature. These arguments also shed light on the long standing debate regarding social risk adjustments in assessments of overall healthcare quality. Finally, we develop an assessment chart to easily visualize disparity patterns and identify the most culpable providers. These methods are demonstrated through analyses of racial disparities in access to transplantation among End-Stage Renal Disease patients.
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The data are available upon request from the OPTN at https://optn.transplant.hrsa.gov/data/view-data-reports/request-data/.
References
Acevedo-Garcia, D., Lochner, K., Osypuk, T., Subramanian, S.: Future directions in residential segregation and health research: a multilevel approach. Am. J. Public Health 93(2), 215–221 (2003). https://doi.org/10.2105/ajph.93.2.215
Agency for Healthcare Research and Quality: National healthcare disparities report. Rockville, MD (2022)
Binger, T., Chen, H., Harder, B.: Hospital rankings and health equity. J. Am. Med. Assoc. 328(18), 1805–1806 (2022). https://doi.org/10.1001/jama.2022.19001
Braveman, P.: Health disparities and health equity: concepts and measurement. Annu. Rev. Public Health 27, 167–194 (2006). https://doi.org/10.1146/annurev.publhealth.27.021405.102103
Daignault, K., Lawson, K., Finelli, A., Saarela, O.: Causal mediation analysis for standardized mortality ratios. Epidemiology 30(4), 532–540 (2019). https://doi.org/10.1097/EDE.0000000000001015
Downing, N.S., Wang, C., Gupta, A., Wang, Y., Nuti, S.V., Ross, J.S., Krumholz, H.M.: Association of racial and socioeconomic disparities with outcomes among patients hospitalized with acute myocardial infarction, heart failure, and pneumonia: an analysis of within- and between-hospital variation. J. Am. Med. Assoc. Netw. Open 1(5), e182044–e182044 (2018). https://doi.org/10.1001/jamanetworkopen.2018.2044
Eggers, P.W.: Racial disparities in access to transplantation: a tough nut to crack. Kidney Int. 76(6), 589–590 (2009). https://doi.org/10.1038/ki.2009.256
Fiscella, K., Franks, P., Gold, M., Clancy, C.: Inequality in quality: addressing socioeconomic, racial, and ethnic disparities in health care. J. Am. Med. Assoc. 289(19), 2579–2584 (2000). https://doi.org/10.1001/jama.283.19.2579
He, K., Kalbfleisch, J., Li, Y., Li, Y.: Evaluating hospital readmission rates in dialysis facilities; adjusting for hospital effects. Lifetime Data Anal. 19(4), 490–512 (2013). https://doi.org/10.1007/s10985-013-9264-6
Howard, R., Cornell, D., Schold, J.: CMS oversight, OPOs and transplant centers and the law of unintended consequences. Clin. Transplant. 23(6), 778–783 (2009). https://doi.org/10.1111/j.1399-0012.2009.01157.x
Jackson, J., Williams, D., VanderWeele, T.: Disparities at the intersection of marginalized groups. Soc. Psychiatry Psychiatr. Epidemiol. 51(10), 1349–1359 (2016). https://doi.org/10.1007/s00127-016-1276-6
Jay, C., Schold, J.D.: Measuring transplant center performance: the goals are not controversial but the methods and consequences can be. Curr. Transpl. Rep. 4(1), 52–58 (2017). https://doi.org/10.1007/s40472-017-0138-9
Jones, H., Spiegelhalter, D.: The identification of “unusual” health-care providers from a hierarchical model. Am. Stat. 65(3), 154–163 (2011). https://doi.org/10.1198/tast.2011.10190
Kalbfleisch, J., Wolfe, R.: On monitoring outcomes of medical providers. Stat. Biosci. 5(2), 286–302 (2013). https://doi.org/10.1007/s12561-013-9093-x
Kalbfleisch, J., Wolfe, R., Bell, S., Sun, R., Messana, J., Shearon, T., Li, Y.: Risk adjustment and the assessment of disparities in dialysis mortality outcomes. J. Am. Soc. Nephrol. 26(11), 2641–2645 (2015). https://doi.org/10.1681/ASN.2014050512
Kalbfleisch, J., He, K., Xia, L., Li, Y.: Does the inter-unit reliability (IUR) measure reliability? Health Serv. Oucomes Res. Methodol. 18, 215–225 (2018). https://doi.org/10.1007/s10742-018-0185-4
Keele, L., Stevenson, R.: Causal interaction and effect modification: same model, different concepts. Polit. Sci. Res. Methods 9, 641–649 (2021). https://doi.org/10.1017/psrm.2020.12
Ku, E., Lee, B., McCulloch, C., Roll, G., Grimes, B., Adey, D.: Racial and ethnic disparities in kidney transplant access within a theoretical context of medical eligibility. Transplantation 104(7), 1437–1444 (2020). https://doi.org/10.1097/TP.0000000000002962
Kulkarni, S., Ladin, K., Haakinson, D., Greene, E., Li, L., Deng, Y.: Association of racial disparities with access to kidney transplant after the implementation of the new kidney allocation system. J. Am. Med. Assoc. 154(7), 618–625 (2019). https://doi.org/10.1001/jamasurg.2019.0512
Lloren, A., Liu, S., Herrin, J., Lin, Z., Zhou, G., Wang, Y., Bernheim, S.: Measuring hospital-specific disparities by dual eligibility and race to reduce health inequities. Health Serv. Res. 54(Suppl 1), 243–254 (2019). https://doi.org/10.1111/1475-6773.13108
Mentias, A., Peterson, E., Keshvani, N., Kumbhani, D., Yancy, C., Morris, A., Pandey, A.: Achieving equity in hospital performance assessments using composite race-specific measures of risk-standardized readmission and mortality rates for heart failure. Circulation 147(15), 1121–1133 (2023). https://doi.org/10.1161/CIRCULATIONAHA.122.061995
National Quality Forum: Risk adjustment for socioeconomic status or other sociodemographic factors. (2014). https://www.qualityforum.org/Publications/2014/08/Risk_Adjustment_for_Socioeconomic_Status_or_Other_Sociodemographic_Factors.aspx
National Quality Forum: A roadmap for promoting health equity and eliminating disparities: the four I’s for health equity. (2017). https://www.qualityforum.org/Publications/2017/09/A_Roadmap_for_Promoting_Health_Equity_and_Eliminating_Disparities__The_Four_I_s_for_Health_Equity.aspx
National Research Council: Realizing the promise of equity in the organ transplantation system. The National Academies Press, Washington, DC (2022)
Normand, S.L.T., Shahian, D.M.: Statistical and clinical aspects of hospital outcomes profiling. Stat. Sci. 22(2), 206–226 (2007). https://doi.org/10.1214/088342307000000096
Organ Procurement and Transplantation Network: OPTN board approves elimination of race-based calculation for transplant candidate listing. (2022). https://optn.transplant.hrsa.gov/news/optn-board-approves-elimination-of-race-based-calculation-for-transplant-candidate-listing/
Park, C., Jones, M., Kaplan, S., Koller, F., Wilder, J., Boulware, L., McElroy, L.M.: A scoping review of inequities in access to organ transplant in the United States. Int. J. Equity Health (2022). https://doi.org/10.1186/s12939-021-01616-x
Rathore, S., Krumholz, H.: Differences, disparities, and biases: clarifying racial variations in health care use. Ann. Intern. Med. 141(8), 635–638 (2004). https://doi.org/10.7326/0003-4819-141-8-200410190-00011
Scientific Registry of Transplant Recipients: Technical methods for the program-specific reports. (2022). https://www.srtr.org/about-the-data/technical-methods-for-the-program-specific-reports/
Silber, J., Rosenbaum, P., Ross, R., Ludwig, J., Wang, W., Niknam, B.A., Fleisher, L.A.: A hospital-specific template for benchmarking its cost and quality. Health Serv. Res. 49(5), 1475–1497 (2014). https://doi.org/10.1111/1475-6773.12226
Smith, D.: The racial segregation of hospital care revisited: medicare discharge patterns and their implications. Am. J. Public Health 88(3), 461–463 (1998). https://doi.org/10.2105/ajph.88.3.461
Spiegelhalter, D., Sherlaw-Johnson, C., Bardsley, M., Blunt, I., Wood, C., Grigg, O.: Statistical methods for healthcare regulation: rating, screening and surveillance. J. Roy. Stat. Soc. 175(1), 1–47 (2012). https://doi.org/10.1111/j.1467-985X.2011.01010.x
Tang, T., Austin, P., Lawson, K., Finelli, A., Saarela, O.: Constructing inverse probability weights for institutional comparisons in healthcare. Stat. Med. 39(23), 3156–3172 (2020). https://doi.org/10.1002/sim.8657
The Centers for Medicare and Medicaid Services: CMS Disparity Methods Confidential Reporting Methodology. (2023). https://qualitynet.cms.gov/inpatient/measures/disparity-methods/methodology
Trivedi, A.N., Nsa, W., Hausmann, L.R., Lee, J.S., Ma, A., Bratzler, D.W., Fine, M.J.: Quality and equity of care in U.S. hospitals. N. Engl. J. Med. 371(24), 2298–2308 (2014). https://doi.org/10.1056/NEJMsa1405003
Valeri, L., Proust-Lima, C., Fan, W., Chen, J., Jacqmin-Gadda, H.: A multistate approach for the study of interventions on an intermediate time-to-event in health disparities research. Stat. Methods Med. Res. 32(8), 1445–1460 (2023). https://doi.org/10.1177/09622802231163331
VanderWeele, T.: On the distinction between interaction and effect modification. Epidemiology 20(6), 863–871 (2009)
Varewyck, M., Goetghebeur, E., Eriksson, M., Vansteelandt, S.: On shrinkage and model extrapolation in the evaluation of clinical center performance. Biostatistics 15(4), 651–654 (2014). https://doi.org/10.1093/biostatistics/kxu019
Varewyck, M., Vansteelandt, S., Eriksson, M., Goetghebeur, E.: On the practice of ignoring center-patient interactions in evaluating hospital performance. Stat. Med. 35(2), 227–238 (2016). https://doi.org/10.1002/sim.6634
White, K., Haas, J., Williams, D.: Elucidating the role of place in health care disparities: the example of racial/ethnic residential segregation. Health Serv. Res. 47(3pt2), 1278–1299 (2012). https://doi.org/10.1111/j.1475-6773.2012.01410.x
Williams, D., Rucker, T.: Understanding and addressing racial disparities in health care. Health Care Financ. Rev. 21(4), 75–90 (2000)
Wolfe, R., Ashby, V., Milford, E., Ojo, A., Ettenger, R., Agodoa, L., Port, F.: Comparison of mortality in all patients on dialysis, patients on dialysis awaiting transplantation, and recipients of a first cadaveric transplant. N. Engl. J. Med. 341, 1725–1730 (1999). https://doi.org/10.1056/NEJM199912023412303
Xia, L., He, K., Li, Y., Kalbfleisch, J.: Accounting for total variation and robustness in profiling health care providers. Biostatistics 23, 257–273 (2022). https://doi.org/10.1093/biostatistics/kxaa024
Acknowledgements
The authors thank Dr. Kevin He for his helpful comments and for providing the OPTN dataset.
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This work was supported in part by Health Resources and Services Administration contract HHSH250-2019-00001C. The content is the responsibility of the authors alone and does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.
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NH conceived of the statistical concepts and performed the analyses. NH and CD developed the interpretation and discussion of the proposed framework, and approved of the final written manuscript.
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Hartman, N., Dahlerus, C. Evaluating medical providers in terms of patient health disparities: a statistical framework. Health Serv Outcomes Res Method (2024). https://doi.org/10.1007/s10742-024-00323-8
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DOI: https://doi.org/10.1007/s10742-024-00323-8