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Consult Pharm ; 28(2): 99-109, 2013 Feb.
Article in English | MEDLINE | ID: mdl-23395810

ABSTRACT

OBJECTIVE: To determine the utility (i.e., positive predictive value [PPV] and time requirement) of an adverse drug event (ADE) trigger tool in Veterans Affairs (VA) nursing facilities and to describe the most common types of potential ADEs detected with the trigger tool. DESIGN: Retrospective chart review. SETTING/PATIENTS: Veterans residing in three VA nursing facilities between September 29, 2010, and October 29, 2010. MEASUREMENT: We used the Institute for Healthcare Improvement-endorsed nursing facility ADE trigger tool, modified to enhance its clinical relevance to detect potential ADEs. Electronic medical records were screened to identify residents with one or more abnormal laboratory values specified in the trigger tool. MAIN OUTCOME MEASURES: A potential ADE was defined as the concurrent administration of medication that could cause the abnormal laboratory value. An overall PPV, or proportion of residents with an abnormal laboratory value who had a potential ADE, and average time required to complete each trigger tool assessment, were calculated. RESULTS: Among 321 veterans, 50.5% (n = 162) had at least one abnormal laboratory value contained in the trigger tool. Ninety-nine potential ADEs involving 146 medications were detected in 65 veterans. The overall PPV of the ADE trigger tool was 40.1% (65/162), and the average time to complete resident assessments was 8.8 (standard deviation ± 5.7) minutes. The most common potential ADEs were acute kidney injury (n = 30 residents), hypokalemia (n = 18), hypoglycemia (n = 13), and hyperkalemia (n = 10). CONCLUSIONS: The modified nursing facility trigger tool was shown to be an effective and efficient method for detecting potential ADEs.


Subject(s)
Drug-Related Side Effects and Adverse Reactions , Drug-Related Side Effects and Adverse Reactions/diagnosis , Nursing Homes , Aged , Aged, 80 and over , Drug-Related Side Effects and Adverse Reactions/epidemiology , Electronic Health Records , Female , Humans , Male , Middle Aged , Predictive Value of Tests , Retrospective Studies , Time Factors , United States , United States Department of Veterans Affairs , Veterans
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