STUDY OBJECTIVE: To evaluate the potential ability of computerized information systems (ISs) to identify and prevent adverse events in medical patients. DESIGN: Clinical descriptions of all 133 adverse events identified through chart review for a cohort of 3,138 medical patients were evaluated by two reviewers. MEASUREMENTS: For each adverse event, three hierarchical levels of IS sophistication were considered: Level 1--demographics, results for all diagnostic tests, and current medications would be available on-line; Level 2--all orders would be entered on-line by physicians; and Level 3--additional clinical data, such as automated problem lists, would be available on-line. Potential for event identification and potential for event prevention were scored by each reviewer according to two distinct sets of event monitors. RESULTS: 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.
STUDY OBJECTIVE: To evaluate the potential ability of computerized information systems (ISs) to identify and prevent adverse events in medical patients. DESIGN: Clinical descriptions of all 133 adverse events identified through chart review for a cohort of 3,138 medical patients were evaluated by two reviewers. MEASUREMENTS: For each adverse event, three hierarchical levels of IS sophistication were considered: Level 1--demographics, results for all diagnostic tests, and current medications would be available on-line; Level 2--all orders would be entered on-line by physicians; and Level 3--additional clinical data, such as automated problem lists, would be available on-line. Potential for event identification and potential for event prevention were scored by each reviewer according to two distinct sets of event monitors. RESULTS: 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.
Authors: Tejal K Gandhi; Saul N Weingart; Andrew C Seger; Joshua Borus; Elisabeth Burdick; Eric G Poon; Lucian L Leape; David W Bates Journal: J Gen Intern Med Date: 2005-09 Impact factor: 5.128