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)

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

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

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 Agency for Healthcare Research and Quality, Rockville, MD.

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.

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

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

Hospital “Quality” Hospital intercept term

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

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

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

Impact of Regionalization

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

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

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

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

NNE Cardiovascular Study O’Connor GT. JAMA 1996.

Current Project

Project Officer Michael Handrigan, PhD

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