PURPOSE: To evaluate the performance of using trigger words (e.g. clues to an adverse drug reaction) in unstructured, narrative text to detect adverse drug reactions (ADRs) and compare the use of these trigger words to a targeted chart review for ADR detection within the intensive care unit (ICU) discharge summary note. MATERIALS: A retrospective medical record review was conducted. Evaluation of ADRs occurred in two phases - targeted chart review of the ICU discharge summary notes in Phase 1 and targeted chart review using specific words and phrases as triggers for ADRs in Phase 2. RESULTS: Four hundred ADRs were documented in 223 patients for Phase 1. For Phase 2, there were 219 ADRs identified in 120 patients. 138 real or accurate ADRs were identified from Phase 1 and 47 duplicate events. 34 ADRs from Phase 2 were not identified in Phase 1. Fifteen of the ADRs were inaccurately presumed in Phase 2. Fifty-eight of 127 text triggers identified at least one ADR. Low and moderate frequency trigger words were more likely to have PPVs > 5%. CONCLUSIONS: Targeted chart review using specific words and phrases as triggers for ADRs is a reasonable approach to identify ADRs and may save time compared to other methods after further refinement leads to a more accurately performing trigger word list.
PURPOSE: To evaluate the performance of using trigger words (e.g. clues to an adverse drug reaction) in unstructured, narrative text to detect adverse drug reactions (ADRs) and compare the use of these trigger words to a targeted chart review for ADR detection within the intensive care unit (ICU) discharge summary note. MATERIALS: A retrospective medical record review was conducted. Evaluation of ADRs occurred in two phases - targeted chart review of the ICU discharge summary notes in Phase 1 and targeted chart review using specific words and phrases as triggers for ADRs in Phase 2. RESULTS: Four hundred ADRs were documented in 223 patients for Phase 1. For Phase 2, there were 219 ADRs identified in 120 patients. 138 real or accurate ADRs were identified from Phase 1 and 47 duplicate events. 34 ADRs from Phase 2 were not identified in Phase 1. Fifteen of the ADRs were inaccurately presumed in Phase 2. Fifty-eight of 127 text triggers identified at least one ADR. Low and moderate frequency trigger words were more likely to have PPVs > 5%. CONCLUSIONS: Targeted chart review using specific words and phrases as triggers for ADRs is a reasonable approach to identify ADRs and may save time compared to other methods after further refinement leads to a more accurately performing trigger word list.
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Keywords:
Drug-related side effects and adverse reactions; computerized; critical care; intensive care units; medical informatics applications; medical record systems; medication errors; patient safety
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