Outlier payments for cardiac surgery and hospital quality

Health Affairs

Volumn 28, Issue 4, 2009, Pages 1154-1160

  Baser, Onur ^a   Fan, Zhahoui ^a   Dimick, Justin B ^a   Staiger, Douglas O ^b   Birkmeyer, John D ^a  

^a UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

^b DARTMOUTH INSTITUTE FOR HEALTH POLICY AND CLINICAL PRACTICE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGED; ARTICLE; BILLING AND CLAIMS; CONTROLLED STUDY; CORONARY ARTERY BYPASS GRAFT; DIAGNOSIS RELATED GROUP; FEMALE; HEALTH CARE COST; HEALTH CARE QUALITY; HEALTH INSURANCE; HOSPITAL BILLING; HOSPITAL CARE; HUMAN; MAJOR CLINICAL STUDY; MALE; MEDICARE; MORBIDITY; MORTALITY; PROSPECTIVE PAYMENT; UNITED STATES;

ACCOUNTS PAYABLE AND RECEIVABLE; CARDIAC SURGICAL PROCEDURES; CORONARY ARTERY BYPASS; HOSPITALS; HUMANS; INSURANCE CLAIM REPORTING; INSURANCE, HEALTH, REIMBURSEMENT; MEDICARE; QUALITY ASSURANCE, HEALTH CARE; UNITED STATES;

EID: 67651202204     PISSN: 02782715     EISSN: 15445208     Source Type: Journal    
DOI: 10.1377/hlthaff.28.4.1154     Document Type: Article

References (20)

1. Centers for Medicare and Medicaid Services, "Acute Inpatient PPS Outlier Payments," October 2006, http://www.cms.hhs.gov/AcuteInpatientPPS/ 04-outlier.asp (accessed 9 April 2009).
2. Medicare fiscal intermediaries determine hospital CCRs based on cost reports filed by hospitals. The CCR represents the estimated true costs of services (within defined categories) listed on the hospital's cost report, divided by gross charges in effect during the cost report period.
3. R. Moynihan, "Another U.S. Healthcare Giant Is Hit by Scandal," BMJ 327, no. 7424 (2003): 1128;
4. E. Silverman, "Tough Negotiations in Store between Plans and Hospitals," Managed Care 12, no. 10 (2003): 42-45;
5. and "The Real Tenet Scandal," Wall Street Journal, 31 December 2002.
6. Among other changes, the CMS closed a long-standing accounting loophole often exploited by hospitals. In previous years, hospitals were allowed to use the statewide average CCR if their own CCRs fell outside three standard deviations from the statewide average. By raising their charges sufficiently, hospitals could reduce their CCRs low enough to trigger the statewide average provision. In this scenario, a hospital's very high covered charges would be multiplied by a much higher CCR, leading to a substantial overstatement of covered costs and much higher outlier payments. The CMS eliminated this statewide average provision in 2003.
7. A. Elixhauser et al., "Comorbidity Measures for Use with Administrative Data," Medical Care 36, no. 1 (1998): 8-27.
8. J.M. Wooldridge, Econometric Analysis of Cross Section and Panel Data (Cambridge, Mass.: MIT Press, 2002).
9. Based on hierarchical models and empirical Bayes techniques, this composite measure predicts a hospital's true risk-adjusted mortality by combining two important measures: its actual risk-adjusted mortality and its procedure volume. The weight placed on each input varies across hospitals, with more weight placed on mortality when it was measured reliably (that is, at hospitals that have higher caseloads). The remaining weight is then placed on hospital volume, thus accounting for empirical relationships between volume and mortality with this procedure. This approach ensures an optimal combination of these two measures, as the direct measure (mortality) is weighted to the extent it is reliable, and the proxy measure (volume) is weighted only to the extent necessary. D.O. Staiger et al., "Empirically Derived Composite Measures of Surgical Performance," Medical Care 47, no. 2 (2009): 226-233;
10. and T.A.B. Snijders and R.J. Bosker, Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (California: Sage Publications, 1999).
11. Ibid.
12. E.V. Finlayson et al., "Adjusting Surgical Mortality Rates for Patient Comorbidities: More Harm than Good?" Surgery 132, no. 5 (2002): 787-794;
13. L.I. Iezzoni et al., "Chronic Conditions and Risk of In-Hospital Death," Health Services Research 29, no. 4 (1994): 435-460;
14. and M. Shwartz et al., "The Importance of Comorbidities in Explaining Differences in Patient Costs," Medical Care 34, no. 8 (1996): 767-782.
15. E.S. Fisher, "The Accuracy of Medicare's Hospital Claims Data: Progress Has Been Made, but Problems Remain," American Journal of Public Health 82, no. 2 (1992): 243-248;
16. J.A. Baron et al., "Internal Validation of Medicare Claims Data," Epidemiology 5, no. 5 (1994): 541-544;
17. and D.J. Malenka et al., "Using Administrative Data to Describe Case-mix: A Comparison with the Medical Record," Journal of Clinical Epidemiology 47, no. 9 (1994): 1027-1032.
18. J.B. Dimick and J.D. Birkmeyer, "Ranking Hospitals on Surgical Quality: Does Risk-Adjustment Always Matter?" Journal of the American College of Surgeons 207, no. 3 (2008): 347-351.
19. Effective 1 October 2008, as mandated by the Deficit Reduction Act of 2005, the CMS will require Medicare-participating hospitals to disclose all hospital-acquired conditions (HACs). For HACs and the included "never events," the CMS will pay Medicare-participating hospitals as though the secondary diagnosis, or never event, was not present. See Center for Medicare Advocacy, "CMS to Hospitals: If It Should Never Happen, We Will Never Pay," http://www.medicareadvocacy.org/Reform-08-09.25.NeverEvents.htm (accessed 9 April 2009).
20. G. Hackbarth, R. Reischauer, and A. Mutti, "Collective Accountability for Medical Care - Toward Bundled Medicare Payments," New England Journal of Medicine 359, no. 1 (2008): 3-5.