Meta-analysis of Interventions to Reduce Adverse Drug Reactions in Older Adults

Abstract

Objectives: To examine the effect of interventions to optimize medication use on adverse drug reactions (ADRs) in older adults.

Design: Systematic review and meta-analysis. EMBASE, PubMed, OVID, Cochrane Library, Clinicaltrials.gov, and Google Scholar were searched through April 30, 2017.

Setting: Randomized controlled trials.

Participants: Older adults (mean age ≥65) taking medications.

Measurements: Two authors independently extracted relevant information and assessed studies for risk of bias. Discrepancies were resolved in consensus meetings. The outcomes were any and serious ADRs. Random-effects models were used to combine the results of multiple studies and create summary estimates.

Results: Thirteen randomized controlled trials involving 6,198 older adults were included. The studies employed a number of different interventions that were categorized as pharmacist-led interventions (8 studies), other health professional-led interventions (3 studies), a brief educational session (1 study), and a technology intervention (1 study). The intervention group was 21% less likely than the control group to experience any ADR (odds ratio (OR) = 0.79, 95% confidence interval (CI) = 0.62-0.99). In the six studies that examined serious ADRs, the intervention group was 36% less likely than the control group to experience a serious ADR (OR = 0.64, 95% CI = 0.42-0.98).

Conclusion: Interventions designed to optimize medication use reduced the risk of any and serious ADRs in older adults. Implementation of these successful interventions in healthcare systems may improve medication safety in older adults.

Keywords: adverse drug reaction; aged; meta-analysis; randomized controlled trials.

Figure 1

PRISMA flow diagram of the selection of eligible studies.

Figure 2

Forest plot of the intervention effects on the likelihood of experiencing any adverse drug reaction. Pooled estimates (diamond) calculated by the random effects model for pooling the individual log odds ratios and obtaining an overall estimate that incorporates between-study heterogeneity.

Figure 3

Forest plot of the intervention effects on the likelihood of experiencing a serious adverse drug reaction. Pooled estimates (diamond) calculated by the random effects model for pooling the individual log odds ratios and obtaining an overall estimate that incorporates between-study heterogeneity.