Consensus List of Signals to Detect Potential Adverse Drug Reactions in Nursing Homes

Abstract

OBJECTIVES: To develop a consensus list of agreed‐upon laboratory, pharmacy, and Minimum Data Set signals that a computer system can use in the nursing home to detect potential adverse drug reactions (ADRs). DESIGN: Literature search for potential ADR signals, followed by an internet‐based, a two‐round, modified Delphi survey. SETTING: A nationally representative survey of experts in geriatrics. PARTICIPANTS: Panel of 13 physicians, 10 pharmacists, and 13 advanced practitioners. MEASUREMENTS: Mean score and 95% confidence interval (CI) for each of 80 signals rated on a 5‐point Likert scale (5=strong agreement with likelihood of indicating potential ADRs). Consensus agreement indicated by a lower‐limit 95% CI of 4.0 or greater. RESULTS: Panelists reached consensus agreement on 40 signals: 15 laboratory and medication combinations, 12 medication concentrations, 10 antidotes, and three Resident Assessment Protocols (RAPs). Highest consensus scores (4.6, 95% CI=4.4–4.9 or 4.4–4.8) were for naloxone when taking opioid analgesics; phytonadione when taking warfarin; dextrose, glucagon, or liquid glucose when taking hypoglycemic agents; medication‐induced hypoglycemia; supratherapeutic international normalized ratio when taking warfarin; and triggering the Falls RAP when taking certain medications. CONCLUSION: A multidisciplinary expert panel was able to reach consensus agreement on a list of signals to detect potential ADRs in nursing home residents. The results of this study can be used to prioritize an initial list of signals to be included in paper‐ or computer‐based methods for potential ADR detection.