DEFINING QUALITY OF PERIOPERATIVE CARE BY STATISTICAL PROCESS-CONTROLOF ADVERSE OUTCOMES

Background: Through peer review, we separated the contributions of sys tem error and human (anesthesiologist) error to adverse perioperative outcomes. In addition, we monitored the quality of our perioperative c are by statistically defining a predictable rate of adverse outcome de pendent on the system in which practice occurs and respondent to any s pecial causes for variation. Methods: Traditional methods of identifyi ng human errors using peer review were expanded to allow identificatio n of system errors in cases involving one or more of the anesthesia cl inical indicators recommended in 1992 by the Joint Commission on Accre ditation of Healthcare Organizations. Outcome data also were subjected to statistical process control analysis, an industrial method that us es control charts to monitor product quality and variation. Results: O f 13,389 anesthetics, 110 involved one or more clinical indicators of the Joint Commission on Accreditation of Healthcare Organizations. Pee r review revealed that 6 of 110 cases involved two separate errors. Of these 116 errors, 9 (7.8%) were human errors and 107 (92.2%) were sys tem errors. Attribute control charts demonstrated all indicators, exce pting one (fulminant pulmonary edema), to be in statistical control. C onclusions: The major determinant of our patient care quality is the s ystem through which services are delivered and not the individual anes thesia care provider. Outcome of anesthesia services and perioperative care is in statistical control and therefore stable. A stable system has a measurable, communicable capability that allows description and prediction of the quality of care we provide on a monthly basis.