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.
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.
Authors: J H Gurwitz; T S Field; J Avorn; D McCormick; S Jain; M Eckler; M Benser; A C Edmondson; D W Bates Journal: Am J Med Date: 2000-08-01 Impact factor: 4.965
Authors: Jerry H Gurwitz; Terry S Field; James Judge; Paula Rochon; Leslie R Harrold; Cynthia Cadoret; Monica Lee; Kathleen White; Jane LaPrino; Janet Erramuspe-Mainard; Martin DeFlorio; Linda Gavendo; Jill Auger; David W Bates Journal: Am J Med Date: 2005-03 Impact factor: 4.965
Authors: Rainu Kaushal; David W Bates; Eric G Poon; Ashish K Jha; David Blumenthal Journal: Health Aff (Millwood) Date: 2005 Sep-Oct Impact factor: 6.301
Authors: Rainu Kaushal; David Blumenthal; Eric G Poon; Ashish K Jha; Calvin Franz; Blackford Middleton; John Glaser; Gilad Kuperman; Melissa Christino; Rushika Fernandopulle; Joseph P Newhouse; David W Bates Journal: Ann Intern Med Date: 2005-08-02 Impact factor: 25.391
Authors: Marsha A Raebel; Nikki M Carroll; Susan E Andrade; Elizabeth A Chester; Jennifer Elston Lafata; Adrianne Feldstein; Margaret J Gunter; Winnie W Nelson; Steven R Simon; K Arnold Chan; Robert L Davis; Richard Platt Journal: Am J Manag Care Date: 2006-05 Impact factor: 2.229
Authors: Steven M Handler; Joseph T Hanlon; Subashan Perera; Melissa I Saul; Douglas B Fridsma; Shyam Visweswaran; Stephanie A Studenski; Yazan F Roumani; Nicholas G Castle; David A Nace; Michael J Becich Journal: AMIA Annu Symp Proc Date: 2008-11-06
Authors: Amit Acharya; Pedro Hernandez; Thankam Thyvalikakath; Harold Ye; Mei Song; Titus Schleyer Journal: Int J Med Inform Date: 2013-07-06 Impact factor: 4.046
Authors: Kate L Lapane; Carmel M Hughes; Lori A Daiello; Kathleen A Cameron; Janice Feinberg Journal: J Am Geriatr Soc Date: 2011-06-07 Impact factor: 5.562
Authors: Joseph T Hanlon; Sherrie L Aspinall; Todd P Semla; Steven D Weisbord; Linda F Fried; C Bernie Good; Michael J Fine; Roslyn A Stone; Mary Jo V Pugh; Michelle I Rossi; Steven M Handler Journal: J Am Geriatr Soc Date: 2008-12-10 Impact factor: 5.562