Better-than-average and worse-than-average hospitals may not significantly differ from average hospitals: An analysis of Medicare Hospital Compare ratings

BMJ Quality and Safety

Volumn 24, Issue 2, 2015, Pages 128-134

  Paddock, Susan M ^a   Adams, John L ^b   De La Guardia, Fernando Hoces ^a  

^a RAND CORPORATION   (United States)

^b KAISER PERMANENTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COMPARATIVE STUDY; CONSUMER; HOSPITAL CARE; HOSPITAL READMISSION; MEDICARE; MORTALITY; OUTCOME ASSESSMENT; HEALTH CARE QUALITY; HOSPITAL; HOSPITAL MORTALITY; HUMAN; STANDARDS; STATISTICS AND NUMERICAL DATA; UNITED STATES;

HOSPITAL MORTALITY; HOSPITALS; HUMANS; MEDICARE; PATIENT READMISSION; QUALITY INDICATORS, HEALTH CARE; QUALITY OF HEALTH CARE; UNITED STATES;

EID: 84921666137     PISSN: 20445415     EISSN: None     Source Type: Journal    
DOI: 10.1136/bmjqs-2014-003405     Document Type: Article

References (25)

1. Agency for Healthcare Research and Quality. Health Care Reporting Compendium 2014 [accessed 2014 July 9]. https://www.cahps.ahrq.gov/apps/rcc.aspx
2. Friedberg MW, Damberg CL. Methodological considerations in generating provider performance scores for use in public reporting: a guide for community quality collaboratives. AHRQ Pub. No. 11-0093, Rockville, MD: Agency for Healthcare Research and Quality, 2011.
3. Fung CH, Lim YW, Mattke S, et al. Systematic review: the evidence that publishing patient care performance data improves quality of care. Ann Intern Med 2008;148:111-23.
4. Calikoglu S, Murray R, Feeney D. Hospital pay-for-performance programs in Maryland produced strong results, including reduced hospital-acquired conditions. Health Aff (Millwood) 2012;31:2649-58.
5. Ryan AM, Nallamothu BK, Dimick JB. Medicare's public reporting initiative on hospital quality had modest or no impact on mortality from three key conditions. Health Aff (Millwood) 2012;31:585-92.
6. Hibbard JH. What can we say about the impact of public reporting? Inconsistent execution yields variable results. Ann Intern Med 2008;148:160-1.
7. Sinaiko AD, Eastman D, Rosenthal MB. How report cards on physicians, physician groups, and hospitals can have greater impact on consumer choices. Health Aff 2012;31:602-11.
8. Sofaer S, Hibbard J. Best practices in public reporting no. 2: maximizing consumer understanding of public comparative quality reports: effective use of explanatory information, Report No.: Contract No.: AHRQ Publication No. 10-0082-1-EF, Rockville, MD: Agency for Healthcare Research and Quality, 2010.
9. State of California Office of the Patient Advocate. California Health Care Quality Report Cards 2014 [cited 2014 July 3]. http://www.opa.ca.gov/Pages/reportcard.aspx
10. Hibbard JH, Peters E, Dixon A, et al. Consumer competencies and the use of comparative quality information: it isn't just about literacy. Med care Res Rev 2007;64:379-94.
11. Faber M, Bosch M, Wollersheim H, et al. Public reporting in health care: how do consumers use quality-of-care information? A systematic review. Med Care 2009;47:1-8.
12. Gelman A, Stern H. The difference between "significant" and "not significant" is not itself statistically significant. Am Statistician 2006;60:328-31.
13. Schneider EC, Epstein AM. Use of public performance reports: a survey of patients undergoing cardiac surgery. JAMA 1998;279:1638-42.
14. Centers for Medicare and Medicaid Services. Fiscal Year 2009 Quality Measure Reporting for 2010 Payment Update 2008. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Downloads/HospitalRHQDAPU200808.pdf
15. Centers for Medicare and Medicaid Services. 30-day Unplanned Readmission and Death Measures. http://www.medicare.gov/hospitalcompare/Data/30-day-measures.html (accessed 18 Jul 2014).
16. Yale New Haven Health Services Corporation/Center for Outcomes Research and Evaluation (YNHHSC/CORE). 2013 measures updates and specifications: acute myocardial infarction, heart failure, and pneumonia 30-day risk-standardized mortality measure (version 7.0). Centers for Medicare & Medicaid Services (CMS), 2013.
17. Davis MM, Hibbard JH, Milstein A. Consumer tolerance for inaccuracy in physician performance ratings: one size fits none. Issue Brief Cent Stud Health Syst Change 2007;(110):1-5.
18. Bates DW, Gawande AA. The Impact of the internet on quality measurement. Health Aff 2010;19:104-14.
19. Jones HE, Spieglhalter DJ. The identification of "unusual" health-care providers from a hierarchical model. Am Statistician 2011;65:154-63.
20. Adams JL, McGlynn EA, Thomas JW, et al. Incorporating statistical uncertainty in the use of physician cost profiles. BMC Health Serv Res 2010;10:57.
21. Lezzoni LL, ed. Risk adjustment for measuring health care outcomes. 4th edn. Chicago: Health Administration Press, 2013.
22. Marang-van de Mheen PJ, Shojania KG. Simpson's paradox: how performance measurement can fail even with perfect risk adjustment. BMJ Qual Saf 2014;23:701-5.
23. R Core Team. A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing, 2014. http://www.R-project.org
24. Goldstein H, Spiegelhalter DJ. League tables and their limitations: statistical issues in comparisons of institutional performance. J Roy Statist Soc Ser A 1996;159:385-409.
25. Anderson J, Hackman M, Burnich J, et al. Determining hospital performance based on rank ordering: is it appropriate? Am J Med Qual 2007;22:177-85.