Effectiveness of a Calculation-Free Weight-Based Unfractionated Heparin Nomogram With Anti-Xa Level Monitoring Compared With Activated Partial Thromboplastin Time.

BACKGROUND: Accurate monitoring of intravenous unfractionated heparin (UFH) is essential to mitigate the risk of adverse drug events associated with dosing errors. Although recent data support anti-factor Xa (anti-Xa) monitoring preferentially over activated partial thromboplastin time (aPTT) to improve time to therapeutic anticoagulation, the utility of incorporating anti-Xa monitoring with a calculation-free weight-based UFH nomogram has not been formally evaluated. OBJECTIVE: The primary objective of this study was to evaluate the time to therapeutic anticoagulation of a calculation-free weight-based UFH nomogram integrated with anti-Xa monitoring versus a historical control of aPTT monitoring utilizing manual dose calculations. METHODS: This was a retrospective analysis of patients with anti-Xa monitoring and a novel calculation-free weight-based UFH nomogram compared with a historical control with aPTT monitoring and manual calculations. RESULTS: A total of 103 patients in the aPTT cohort and 100 patients in the anti-Xa cohort were analyzed. The anti-Xa cohort achieved goal therapeutic target 3.8 hours sooner than the aPTT cohort (P = 0.03). Patients with anti-Xa monitoring required 1 fewer adjustment per 2.5 patient-days of UFH with the venous thromboembolism nomogram (P = 0.02). Patients in the aPTT cohort required more infusion interruptions because of supratherapeutic values (P = 0.007) and boluses because of subtherapeutic values (P = 0.044). There were no differences in rates of thromboembolism, major bleeding, or clinically relevant nonmajor bleeding between the cohorts. CONCLUSION AND RELEVANCE: This study demonstrated that anti-Xa UFH monitoring integrated with a calculation-free nomogram results in faster time to therapeutic anticoagulation and fewer dose adjustments compared with aPTT monitoring with manual calculations.

Use of Text Searching for Trigger Words in Medical Records to Identify Adverse Drug Reactions within an Intensive Care Unit Discharge Summary.

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.

Improving adverse drug event detection in critically ill patients through screening intensive care unit transfer summaries.

PURPOSE: This study aimed to determine the frequency and type of adverse drug events (ADEs) identified in intensive care unit (ICU) transfer summaries and in the hospital discharge summaries to demonstrate the effectiveness of ICU transfer summary surveillance in the identification of ADEs. METHODS: A retrospective electronic medical record review was conducted for medical ICU patients admitted between January 2009 and April 2009 to a large, academic medical center. The Harvard Practice Scale and the modified Leonard Assessment Scale were used to evaluate the presence of an ADE from the ICU transfer and hospital discharge summaries. RESULTS: Two hundred and fifty-four patients were identified for inclusion with a median medical ICU length of stay of 4.5 days and hospital length of stay of 13 days. The ICU transfer summary review revealed 173 ADEs among 124 unique patients with a rate of 33.9 ADEs per 1000 hospital patient days. Sixty-nine ADEs among 63 unique patients were identified through the hospital discharge summary with a rate of 13.5 ADEs per 1000 hospital patient days. Only 23.1% of ADEs discussed in the ICU transfer summary were also discussed in the hospital discharge summary. CONCLUSIONS: The use of ICU transfer summaries is an effective tool to increase ADE detection. The use of an ICU transfer summary should be considered as an adjunct method to an existing ADE surveillance system for heightened pharmacovigilance.