Potential identifiability and preventability of adverse events using information systems
| Autor: | Anne C. O’Neil, Jonathan M. Teich, Troyen A. Brennan, Glenn M. Chertow, Deborah Boyle, David W. Bates, Anthony L. Komaroff |
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| Rok vydání: | 1994 |
| Předmět: |
medicine.medical_specialty
Drug-Related Side Effects and Adverse Reactions Iatrogenic Disease MEDLINE Health Informatics law.invention Injury Severity Score law Risk Factors medicine Information system Humans Adverse effect Decision Making Computer-Assisted Risk Management Event (computing) business.industry Reproducibility of Results medicine.disease Intensive care unit Emergency medicine Cohort Identifiability Wounds and Injuries Medical emergency business Information Systems Research Article |
| Zdroj: | Journal of the American Medical Informatics Association : JAMIA. 1(5) |
| ISSN: | 1067-5027 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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