Comparison of Three Pharmacovigilance Algorithms in the ICU Setting
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ORIGINAL RESEARCH ARTICLE
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Comparison of Three Pharmacovigilance Algorithms in the ICU Setting A Retrospective and Prospective Evaluation of ADRs Sandra L. Kane-Gill,1,2,3 Elizabeth A. Forsberg,4 Margaret M. Verrico1,2 and Steven M. Handler5,6,7,8 1 Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, USA 2 Department of Pharmacy, University of Pittsburgh Medical Center – Presbyterian/Shadyside, Pittsburgh, PA, USA 3 Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA 4 Department of Pharmacy, University of Pittsburgh Medical Center – St Margaret Hospital, Pittsburgh, PA, USA 5 Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA 6 Geriatric Pharmaceutical Outcomes and Geroinformatics Research and Training Program, Pittsburgh, PA, USA 7 Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA 8 Geriatric Research, Education and Clinical Centers (GRECC) and The Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
Abstract
Background: Pharmacovigilance algorithms are used to assess the likelihood of adverse drug reaction (ADR) occurrence. The preferred instrument for use in the intensive care unit (ICU) is not established. Objective: The primary objective of this study was to compare the agreement between the Kramer algorithm, Naranjo criteria and Jones algorithm for the evaluation of ADRs in the ICU. A secondary objective was to compare the agreement between the same pharmacovigilance algorithms for ADR determination when applied in a retrospective versus concurrent fashion in the ICU. Study Design: There were two phases in this study. Phase I was the retrospective evaluation (i.e. after the patient was discharged from the hospital) conducted in patients admitted during July 2005 to June 2006. Phase II was the concurrent phase (i.e. while the patient was in the hospital) conducted over 6 weeks in 2008. Both phases were conducted at the University of Pittsburgh Medical Center and included adult patients admitted to the medical ICU. Intervention: In phase I, a random sample of 261 medication signals were evaluated individually for potential ADRs using the Kramer algorithm, Naranjo criteria and Jones algorithm. In phase II, an active medication monitoring system was used to detect five abnormal laboratory values, resulting in a random sample of 253 signals that were evaluated using the same three algorithms.
Kane-Gill et al.
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Main Outcome Measure: Percentage agreement among the algorithms for all levels of causality was estimated using a kappa statistic for both phases of the study. Results: For phase I, the kappa values were all >0.7 ranging from 0.721 to 0.855 between instruments, with Naranjo versus Kramer having the highest kappa, which is considered excellent agreement. The kappa statistic
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