Using an anesthesia information management system to prove a deficit in voluntary reporting of adverse events in a quality assurance program

Objective. A deficit is suspected in the manual documentation of adverse ev ents in quality assurance programs in anesthesiology. In order to verify an d quantify this, we retrospectively compared the incidence of manually reco rded perioperative adverse events with automatically detected events. Metho ds. In 1998, data of all anesthetic procedures, including the data set for quality assurance of the German Society of Anaesthesiology and Intensive Ca re Medicine (DGAI), was recorded online with the Anesthesia Information Man agement System (AIMS) NarkoData4 (R) (Imeso GmbH). SQL (Structured Query La nguage) queries based on medical data were defined for the automatic detect ion of common adverse events. The definition of the SQL statements had to b e in accordance with the definition of the DGAI for perioperative adverse e vents: A potentially harmful change of parameters led to therapeutic interv entions by an anesthesiologist. Results. During 16,019 surgical procedures, anesthesiologists recorded 911 (5.7%) adverse events manually, whereas 296 6 (18.7%) events from the same database were detected automatically. With t he exception of hypoxemia, the incidence of automatically detected events w as considerably higher than that of manually recorded events. Fourteen and a half percent (435) of all automatically detected events were recorded man ually. Conclusion. Using automatic detection, we were able to prove a consi derable deficit in the documentation of adverse events according to the gui delines of the German quality assurance program in anesthesiology. Based on the data from manual recording, the results of the quality assurance of ou r department match those of other comparable German departments. Thus, we a re of the opinion that manual incident reporting seriously underestimates t he true occurrence rate of incidents. This brings into question the validit y of quality assurance comparisons based on manually recorded data.