Detection of Intraoperative Incidents by Electronic Scanning of Computerized Anesthesia Records

Abstract

Background The use of a computerized anesthesia information management system provides an opportunity to scan case records electronically for deviations from specific limits for physiologic variables. Anesthesia department policy may define such deviations as intraoperative incidents and may require anesthesiologists to report their occurrence. The actual incidence of such events is not known. Neither is the level of compliance with voluntary reporting. Methods Using automated anesthesia record-keeping with long-term storage, physiologic data were recorded every 15 s from 5,454 patients undergoing noncardiothoracic surgery. Recorded measurements of blood pressure, heart rate, arterial oxygen saturation, and temperature were electronically analyzed for deviations from defined limits. The computer system also was used by anesthesiologists to report voluntarily those deviations as intraoperative incidents. For each electronically detected incident: 1) the complete automated anesthesia record was examined by two senior anesthesiologists who, by consensus, eliminated case records with artifact or in which context suggested that the incident was not clinically relevant, and 2) the anesthesia information management system database was checked for voluntary reporting. Results In 473 automated anesthesia records, 494 incidents were found by electronic scanning of 5,454 automated anesthesia records. Sixty intraoperative incidents were eliminated, 25 due to artifact and 35 due to context. When the remaining 434 intraoperative incidents were checked for voluntary reporting, 18 (4.1%) matching voluntary reports were found. All intraoperative incidents that were reported voluntarily also were detected by electronic scanning. Based on a 10% sample, the sensitivity rate of electronic scanning was 97.2% (35/36), and the specificity rate was 98.4% (427/434). Among 413 cases with electronically detected intraoperative incidents, there were 29 deaths (7.0%), whereas there were only 79 deaths (1.6%) among 5,041 cases without incidents (chi 2 = 58.5, P < 0.001). Conclusions The use of an anesthesia information management system facilitated analysis of intraoperative physiologic data and identified certain intraoperative incidents with high sensitivity and specificity. A low level of compliance with voluntary reporting of defined intraoperative incidents was found for all anesthesiologists studied. Finally, there was a strong association between intraoperative incidents and in-hospital mortality.