BACKGROUND: Older adults take multiple medications and are at high risk for adverse drug effects. OBJECTIVE: This systematic review was conducted to describe the impact of computer decision support (CDS) interventions designed to improve the quality of medication prescribing in older adults. METHODS: PubMed and EMBASE databases were searched from January 1980 through July 2007 (English-language only); studies were eligible if they described a CDS intervention intended to improve medication prescribing in adults aged > or =60 years. Studies were retained if they were observational or experimental in design and reported > or =1 process or clinical outcome measurement related to medication prescribing. In the main analysis, study characteristics and major outcome results were extracted. A combination of searches was performed using relevant medical subject headings: aged; drug therapy, computer-assisted; medication errors; medication errors/prevention and control; decision making, computer-assisted; decision support systems, clinical; and clinical pharmacy information systems. RESULTS: After review of study abstracts, 10 articles met the eligibility criteria. Of those 10 studies testing CDS interventions, 8 showed at least modest improvements (median number needed to treat, 33) in prescribing, as measured by minimizing drugs to avoid, optimizing drug dosage, or more generally improving prescribing choices in older adults (according to each study's intervention protocols). Findings for the impact of CDS interventions on clinical outcomes were mixed and were reported for only 2 studies. CONCLUSIONS: Various types of CDS interventions may be effective in improving medication prescribing in older adults, but few studies reported clinical outcomes related to changes in medication prescribing. Data from this study should help to guide refinement and testing of future CDS interventions that specifically target older adult populations that are taking multiple medications.
BACKGROUND: Older adults take multiple medications and are at high risk for adverse drug effects. OBJECTIVE: This systematic review was conducted to describe the impact of computer decision support (CDS) interventions designed to improve the quality of medication prescribing in older adults. METHODS: PubMed and EMBASE databases were searched from January 1980 through July 2007 (English-language only); studies were eligible if they described a CDS intervention intended to improve medication prescribing in adults aged > or =60 years. Studies were retained if they were observational or experimental in design and reported > or =1 process or clinical outcome measurement related to medication prescribing. In the main analysis, study characteristics and major outcome results were extracted. A combination of searches was performed using relevant medical subject headings: aged; drug therapy, computer-assisted; medication errors; medication errors/prevention and control; decision making, computer-assisted; decision support systems, clinical; and clinical pharmacy information systems. RESULTS: After review of study abstracts, 10 articles met the eligibility criteria. Of those 10 studies testing CDS interventions, 8 showed at least modest improvements (median number needed to treat, 33) in prescribing, as measured by minimizing drugs to avoid, optimizing drug dosage, or more generally improving prescribing choices in older adults (according to each study's intervention protocols). Findings for the impact of CDS interventions on clinical outcomes were mixed and were reported for only 2 studies. CONCLUSIONS: Various types of CDS interventions may be effective in improving medication prescribing in older adults, but few studies reported clinical outcomes related to changes in medication prescribing. Data from this study should help to guide refinement and testing of future CDS interventions that specifically target older adult populations that are taking multiple medications.
Authors: Anna V Medem; Hanna M Seidling; Hans-Georg Eichler; Jens Kaltschmidt; Michael Metzner; Carina M Hubert; David Czock; Walter E Haefeli Journal: Eur J Clin Pharmacol Date: 2017-02-14 Impact factor: 2.953