Potential Identifiability and Preventability of Adverse Events Using Information Systems

Abstract

Of all the adverse events, 53% were judged identifiable using Level 1 information, 58% were judged identifiable using Level 2 information, and 89% were judged identifiable using Level 3 information. The highest-yield event monitors for identifying adverse events were "panic" laboratory results, unexpected transfer to an intensive care unit, and hospital-incurred trauma. With information from Levels 1, 2, and 3, 5%, 13%, and 23% of the adverse events, respectively, were judged preventable. For preventing these adverse events, guided-dose algorithms, drug-laboratory checks, and drug-patient characteristic checks held the most potential.