1. Regionalizing Health Care: Volume Standards vs. Risk-Adjusted Mortality Rate Laurent G. Glance, M.D. Associate Professor Department of Anesthesiology This project was supported by a grant from the Agency for Healthcare and Quality Research (R01 HS 13617)

2. Team members Laurent G Glance, MD (University of Rochester) Turner M. Osler, MD (University of Vermont) Dana B. Mukamel, PhD. (University of California, Irvine) Andrew W. Dick, PhD (RAND) Project officer Yen-Pin Chiang, PhD

3. Scope of the Problem Between 44,000 and 98,000 deaths each year due to medical errors.

4. National Agenda to Improve Patient Safety AHRQ-sponsored report designated “localizing specific surgeries and procedures to high-volume centers” as a High Priority area for patient safety research. Making Health Care Safer: A Critical Analysis of Patient Safety Practices. Evidence Report/Technology Assessment: Number 43. AHRQ Publication No. 01- E058, July 2001. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/clinic/ptsafety/

8. Hypotheses Selective Referral: Selectively referring high-risk surgery patients to high-quality centers will lead to better population outcomes than selectively referring patients to high-volume centers. Selective Avoidance: Diverting high-risk patients from low quality centers will lead to better population outcomes than diverting patients from low-volume centers.

9. Data HCUP California SID (1998-2000) Administrative data (ICD-9-CM codes) 30 diagnoses 21 procedures POA indicator Study Populations CABG PCI AAA surgery

10. Model Development Random-Intercept model Demographics Age, gender, transfer status, admission type (elective vs. non-elective) Comorbidities Disease Staging Elixhauser Comorbidity Algorithm

11. Hospital “Quality” Hospital intercept term

12. Identification of High-Volume and Low-Volume Centers High-Volume based on Leapfrog Criteria AAA > 50 cases/yr CABG > 450 cases/yr PCI > 400 cases/yr Low-Volume Lower volume quartile

13. Estimating Impact of Regionalization Added binary variable to base model to indicate whether a patient was treated at a high-volume center Simulated mortality rate Estimated mortality rate for patients diverted to high-volume centers Observed mortality rate for patients already treated at high-volume centers

15. Volume-Outcome Association Hospital volume is NOT a good proxy for Hospital Quality

17. Impact of Regionalization

18. Findings Selective Referral High-Volume Centers: 0-20% mortality reduction & 70-99% hospital closure High-Quality Centers: 50% mortality reduction & 90-99% hospital closure Selective Avoidance Low-Volume Centers: 0-2.5% reduction in mortality & 25% hospital closure Low-Quality Centers: 2-5% mortality reduction & 1-8% hospital closure

19. Policy Implications Hospital Volume is a POOR Quality Indicator & should not be used as the basis for selective referral or selective avoidance Selective Referral to High-Quality Centers is NOT PRACTICAL Selective Avoidance of Low-Quality Centers may achieve modest reductions in mortality Consider Improving Overall Hospital Quality

20. Quality Improvement based on Feedback of Risk-Adjusted Outcomes NSQIP NNE

21. NSQIP 27% decrease in mortality 45% decrease in morbidity No change in casemix Khuri. Arch Surgery 2002.

22. NNE Cardiovascular Study O’Connor GT. JAMA 1996.

23. Current Project

24. Project Officer Michael Handrigan, PhD

25. Hypothesis Providing trauma and non-trauma centers with information on their risk-adjusted outcomes will lead to improved outcomes.