Using computerized data to identify adverse drug events in outpatients

Citation
B. Honigman et al., Using computerized data to identify adverse drug events in outpatients, J AM MED IN, 8(3), 2001, pp. 254-266
Citations number
46
Categorie Soggetti
Library & Information Science","General & Internal Medicine
Journal title
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
ISSN journal
10675027 → ACNP
Volume
8
Issue
3
Year of publication
2001
Pages
254 - 266
Database
ISI
SICI code
1067-5027(200105/06)8:3<254:UCDTIA>2.0.ZU;2-#
Abstract
Objective: To evaluate the use of a computer program to identify adverse dr ug events (ADEs) in the ambulatory setting and to evaluate the relative con tribution of four computer search methods for identifying ADEs, including d iagnosis codes, allergy rules, computer event monitoring rules, and text se arching. Design: Retrospective analysis of one year of data from an electronic medic al record, including records for 23,064 patients with a primary care physic ian, of whom 15,665 actually came for care. Measurement: Presence of an ADE; sensitivity and specificity of computer se arches for ADE. Results: The computer program identified 25,056 incidents, which were assoc iated with an estimated 864 (95 percent confidence interval [CI], 750-978) ADEs. Thus, the ADE rate was 5.5 (CI, 5.2-5.9) per 100 patients coming for care. Furthermore, in 79 (CI, 68-89) ADEs, the patient required hospitaliza tion, resulting in an estimated rate of 3.4 (CI, 2.7-4.3) admissions per 1, 000 patients. The sensitivity of the search methods for identifying ADEs wa s estimated to be 58 (CI, 18-98) percent, and the estimated specificity was 88 (CI, 87-88) percent. The positive predictive value was 7.5 (CI, 6.5-8.5 ) percent, and the negative predictive value was 99.2 (CI, 95.5-99.98) perc ent. Compared with age and gender-matched controls with no positive screen, patients with ADEs had twice as many outpatient visits and were taking nea rly three times as many drugs. Antihypertensives, ACE-inhibitors, antibioti cs, and diuretics were associated with 56 (CI, 47-65) percent of ADEs. Amon g ADEs, 23 (CI, 16-32) percent were life-threatening or serious, and 38 (CI , 29-47) percent were judged preventable. Conclusion: Computerized search programs can detect ADEs, and free-text sea rches were especially useful. Adverse drug events were frequent, and admiss ions were not rare, although most hospitals today do not identify them. Thu s, such detection programs demonstrate "value-added" for the eledronic reco rd and may be useful for directing and assessing the impact of quality impr ovement efforts.