Defining Quality of Perioperative Care by Statistical Process Control of Adverse Outcomes

Abstract

Background Through peer review, we separated the contributions of system error and human (anesthesiologist) error to adverse perioperative outcomes. In addition, we monitored the quality of our perioperative care by statistically defining a predictable rate of adverse outcome dependent on the system in which practice occurs and respondent to any special causes for variation. Methods Traditional methods of identifying human errors using peer review were expanded to allow identification of system errors in cases involving one or more of the anesthesia clinical indicators recommended in 1992 by the Joint Commission on Accreditation of Healthcare Organizations. Outcome data also were subjected to statistical process control analysis, an industrial method that uses control charts to monitor product quality and variation. Results Of 13,389 anesthetics, 110 involved one or more clinical indicators of the Joint Commission on Accreditation of Healthcare Organizations. Peer 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 system errors. Attribute control charts demonstrated all indicators, excepting one (fulminant pulmonary edema), to be in statistical control. Conclusions The major determinant of our patient care quality is the system through which services are delivered and not the individual anesthesia 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.