Mortality Rate Estimation and Standardization for Public Reporting: Medicare’s Hospital Compare

References

• Allison, J. J., Kiefe, C. I., Weissman, N. W., Person, S. D., Rousculp, M., Canto, J. G., Bae, S., Williams, O. D., Farmer, R., and Centor, R. M. (2000), “Relationship of Hospital Teaching Status with Quality of Care and Mortality for Medicare Patients with Acute MI,” Journal of the American Medical Association, 284, 1256–1262.
   PubMed Web of Science ®Google Scholar
• Ash, A., Fienberg, S. E., Louis, T. L., Normand, S. T., Stukel, T. A., and Utts, J. (2012), “Statistical Issues inHospital Performance,” Commissioned by the Committee of Presidents of Statistical Societies. Available at http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Downloads/Statistical-Issues-in-Assessing-Hospital-Performance.pdf.
   Google Scholar
• Berger, J. O. (1985), Statistical Decision Theory and Bayesian Analysis (2nd ed.), New York: Springer Verlag.
   Google Scholar
• ——— (2006), “The Case for Objective Bayesian Analysis,” Bayesian Analysis, 1, 385–402.
   Web of Science ®Google Scholar
• Box, G. E. P., and Meyer, R. D. (1986), “Dispersion Effects from Fractional Designs,” Technometrics, 28, 19–27.
   Web of Science ®Google Scholar
• Cox, D. R. (1961), “Tests of Separate Families of Hypotheses,” in Proceedings of the Fourth Berkeley Symposium, pp. 105–123.
   Google Scholar
• Dawid, A. P. (1982), “The Well-Calibrated Bayesian,” Journal of the American Statistical Association, 77, 605–610.
   Web of Science ®Google Scholar
• Dimick, J. B., Staiger, D. O., and Birkmeyer, J. D. (2010), “Ranking Hospitals on Surgical Mortality: The Importance of Reliability Adjustment,” Health Services Research, 45, 1614–1629.
   PubMed Web of Science ®Google Scholar
• Gandjour, A., Bannenberg, A., and Lauterbach, K. W. (2003), “Threshold Volumes Associated with Higher Survival in Health Care: A Systematic Review,” Medical Care, 41, 1129–1141.
   PubMed Web of Science ®Google Scholar
• Gelfand, A. E., and Dey, D. K. (1994), “Bayesian Model Choice: Asymptotics and Exact Calculations,” Journal of theRoyal Statistical Society, Series B, 56, 501–514.
   Google Scholar
• Grieco, N., Ieva, F., and Paganoni, A. M. (2012), “Performance Assessment Using Mixed Effects Models: A Case Study on Coronary Patient Care,” IMA Journal of Management Mathematics, 23, 117–131.
   Web of Science ®Google Scholar
• Gu, Y., Fiebig, D. G., Cripps, E., and Kohn, R. (2009), “Bayesian Estimation of A Random Effects Heteroscedastic Probit Model,” Econometrics Journal, 12, 324–339.
   Web of Science ®Google Scholar
• Guglielmi, A., Ieva, F., Paganoni, A. M., Ruggeri, F., and Soriano, J. (2014), “Semiparametric Bayesian Modeling for the Classification of Patients with High Observed Survival Probabilities,” Journal of the Royal Statistical Society, Series C, 63, 25–46.
   Google Scholar
• Halm, E. A., Lee, C., and Chassin, M. R. (2002), “Is Volume Related to Outcome in Health Care? A Systematic Review and Methodologic Critique of the Literature,” Annals of Internal Medicine, 137, 511–520.
   PubMed Web of Science ®Google Scholar
• Hansen, B. B. (2007), “Optmatch: Flexible, Optimal Matching for Observational Studies,” R News, 7, 18–24.
   Google Scholar
• ——— (2008), “Prognostic Analogue of the Propensity Score,” Biometrika, 95, 481–488.
   Web of Science ®Google Scholar
• Kass, R. E., and Raftery, A. E. (1995), “Bayes Factors,” Journal of the American Statistical Association, 90, 773–795.
   Web of Science ®Google Scholar
• Krumholz, H. M., Wang, Y., Mattera, J. A., Wang, Y., Han, L. F., Ingber, M. J., Roman, S., and Normand, S.-L. T. (2006), “An Administrative Claims Model Suitable for Profiling Hospital Performance Based on 30-Day Mortality Rates among Patients with an Acute Myocardial Infarction,” Circulation, 113, 1683–1692.
   PubMed Web of Science ®Google Scholar
• Luft, H. S., Hunt, S. S., and Maerki, S. C. (1987), “The Volume-Outcome Relationship: Practice-Makes-Perfect or Selective-Referral Patterns?” Health Services Research, 22, 157–182.
   PubMed Web of Science ®Google Scholar
• Navathe, A. S., Silber, J. H., Zhu, J., and Volpp, K. G. (2013), “Does Admission to a Teaching Hospital Affect Acute Myocardial Infarction Survival?” Academic Medicine, 88, 475–482.
   PubMed Web of Science ®Google Scholar
• Person, S. D., Allison, J. J., Kiefe, C. I., Weaver, M. T., Williams, O. D., Centor, R. M., and Weissman, N. W. (2004), “Nurse Staffing and Mortality for Medicare Patients with Acute Myocardial Infarction,” Medical Care, 42, 4–12.
   PubMed Web of Science ®Google Scholar
• Polson, N. G., Scott, J. G., and Windle, J. (2013), “Bayesian Inference for Logistic Models Using Polya-Gamma Latent Variables,” Journal of the American Statistical Association, 108, 1339–1349.
   Web of Science ®Google Scholar
• Rosenbaum, P. R. (2010), Design of Observational Studies, New York: Springer.
   Google Scholar
• Rosenbaum, P. R., and Rubin, D. B. (1983), “Constructing a Control Group by Multivariate Matched Sampling Methods that Incorporate the Propensity Score,” American Statistician, 39, 33–38.
   Web of Science ®Google Scholar
• Shahian, D. M., and Normand, S. L. (2003), “The Volume-Outcome Relationship: From Luft to Leapfrog,” Annals of Thoracic Surgery, 75, 1048–1058.
   PubMed Web of Science ®Google Scholar
• Silber, J. H., Rosenbaum, P. R., Brachet, T. J., Ross, R. N., Bressler, L. J., Even-Shoshan, O., Lorch, S. A., and Volpp, K. G. (2010), “The Hospital Compare Mortality Model and the Volume–Outcome Relationship,” Health Services Research, 45, 1148–1167.
   PubMed Web of Science ®Google Scholar
• Silber, J. H., Satopää, V. A., Mukherjee, N., Ročková, V., Wang, W., Hill, A. S., Even-Shoshan, O., Rosenbaum, P. R., and George, E. I. (2016), “Improving Medicare’s HospitalCompare Mortality Model,” Health Services Research, 51, 1229–1247.
   PubMed Web of Science ®Google Scholar
• Spiegelhalter, D., Sherlaw-Johnson, C., Bardsley, M., Blunt, I., Wood, C., and Grigg, O. (2012), “Statistical Methods for Healthcare Regulation: Rating, Screening and Surveillance,” Journal of the Royal Statistical Society, Series A, 175, 1–47.
   Google Scholar
• Stuart, E. A. (2010), “Matching Methods for Causal Inference,” StatisticalScience, 25, 1–21.
   Google Scholar
• Stukel, T. A., Fisher, E. S., Wennberg, D. E., Alter, D. A., Gottlieb, D. J., and Vermeulen, M. J. (2007), “Analysis of Observational Studies in the Presence of Treatment Selection Bias: Effects of Invasive Cardiac Management on AMI Survival Using Propensity Score and Instrumental Variable Methods,” Journal of the American Medical Association, 297, 278–285.
   PubMed Web of Science ®Google Scholar
• Yale New Haven Health Services Corporation. (2014), Measures Updates and Specifications (Version 8.0), Washington, DC: Centers for Medicare and Medicaid Services.
   Google Scholar