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BENCHMARKING AND RISK ADJUSTMENT OF PATIENT OUTCOMES ACROSS ANESTHESIA PROVIDER TEAMS. R Skomra CRNA MS1, D Bacon MD MA1, CA Walawander MA2, and P Knight MD PhD3. 1VA Western New York Health Care System, Buffalo, NY; 2Pharmaceutical Outcomes Research, Inc., Buffalo, NY; 3SUNY at Buffalo, Buffalo, NY. Intr oduction: In our current health care climate, it is becoming more common to compare patient outcome benchmarks across institutions and across providers within an institution. The JCAHO is mandating hospitals to submit standardized outcome measures on a quarterly basis for comparative purposes. In an Anesthesiology Service, the Anesthesiologist and certified nurse anesthetist (CRNA) often work as a team. We evaluated defined benchmarks stratified by teams in addition to individual performance. Methods: A standardized data collection form was completed for all surgical cases in a veteran’s hospital from 7/1/97 to 6/30/98. Data was collected as part of a performance measurement system. Data collected included: patient demographics, anesthesia duration, co-morbidities, and adverse events occurring in the operating room, postanesthesia care unit (PACU) and post-discharge from the recovery unit (within 48 hours of procedure). The outcome measure of interest was the occurrence of an adverse event from the start of anesthesia to 48 hours post discharge from the recovery unit. The rate of occurrence of adverse events for an anesthesia team was risk adjusted based on age, ASA class, ambulatory vs. inpatient procedure, and anesthesia duration. Logistic regression was used to generate predictions. A 95% confidence interval was computed for the standardized adverse event rate across individuals or teams, where a 1 indicates identical observed and predicted adverse event rates. Results: Standardized adverse event rates ranged from 0.79 to 1.23 and 0.71 to 1.29 for individual Anesthesiologists and CRNAs, respectively. None of these values represented statistically significant differences from a standardized rate of 1. Of the 42 anesthesia teams, 21 had a standardized adverse event rate of < 0.71 and 10 had a standardized adverse event rate of > 1.29. However, on evaluation of one anesthesia team, the standardized rate ranged from 0.0 to 3.55 for one Anesthesiologist across multiple CRNAs. The observed rates of adverse events ranged from 0 events to 23.1% of a team’s cases reported to have at least one adverse event. Discussion: As multidisciplinary teams and patient outcomes become more defined, it is important that the effectiveness of the teamwork be evaluated in addition to individual performance. A benchmark database with the ability to risk adjust for case severity is one way to evaluate effectiveness. BENCHMARKING AND RISK ADJUSTMENT OF PATIENT OUTCOMES ACROSS ANESTHESIA PROVIDER TEAMS. R Skomra CRNA MS1, D Bacon MD MA1, CA Walawander MA2, and P Knight MD PhD3. 1VA Western New York Health Care System, Buffalo, NY; 2Pharmaceutical Outcomes Research, Inc., Buffalo, NY; 3SUNY at Buffalo, Buffalo, NY. INTRODUCTION In our current climate of health care, more and more national and professional organizations and accrediting agencies are requiring health care organizations to re-evaluate their processes of care and to collect clinical outcome data to assist in the documentation of process and patient improvements of care. Physician profiling is becoming common practice where a physician is provided feedback on a particular patient outcome and is ranked in relation to other physicians within the practice. This feedback is used to spark a dynamic educational process whereby ideally a process is improved and a best practice is established. However, a physician rarely works alone in their capacity of providing care. In the surgical center, it is often the case that a nurse anesthetist will work along side or under the supervision of an anesthesiologist. In this analysis, the rate of adverse events over a one year time period were compared across individual anesthesia providers, but also across the anesthesiologist/nurse anesthetist team to evaluate the variance of patient outcomes across teams.