Potential identifiability and preventability of adverse events using information systems.
OBJECTIVE
To evaluate the potential ability of computerized information systems (ISs) to identify and prevent adverse events in medical patients.


METHODS
Clinical descriptions of all 133 adverse events identified through chart review for a cohort of 3,138 medical patients were evaluated by two reviewers.


METHODS
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.
Bates
D W
DW
Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115.
O'Neil
A C
AC
Boyle
D
D
Teich
J
J
Chertow
G M
GM
Komaroff
A L
AL
Brennan
T A
TA
D003658:Decision Making, Computer-Assisted; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D007049:Iatrogenic Disease / Q000517:prevention & control*; D007256:Information Systems / Q000592:standards*; D015601:Injury Severity Score; D015203:Reproducibility of Results; D012307:Risk Factors; D012308:Risk Management / Q000379:methods*; D014947:Wounds and Injuries / Q000145:classification / Q000517:prevention & control*