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 2001. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/clinic/ptsafety/

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 (1998-2000) Administrative data (ICD-9-CM codes)

30 diagnoses 21 procedures POA indicator

Study Populations CABG PCI AAA surgery

Model Development

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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 OfficerMichael Handrigan, PhD

Hypothesis

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