Impact of strategies to reduce polypharmacy on clinically relevant endpoints: a systematic review and meta-analysis

Abstract

Aim: The aim of the present study was to explore the impact of strategies to reduce polypharmacy on mortality, hospitalization and change in number of drugs.

Methods: Systematic review and meta-analysis: a systematic literature search targeting patients ≥65 years with polypharmacy (≥4 drugs), focusing on patient-relevant outcome measures, was conducted. We included controlled studies aiming to reduce polypharmacy. Two reviewers independently assessed studies for eligibility, extracted data and evaluated study quality.

Results: Twenty-five studies, including 10 980 participants, were included, comprising 21 randomized controlled trials and four nonrandomized controlled trials. The majority of the included studies aimed at improving quality or the appropriateness of prescribing by eliminating inappropriate and non-evidence-based drugs. These strategies to reduce polypharmacy had no effect on all-cause mortality (odds ratio 1.02; 95% confidence interval 0.84, 1.23). Only single studies found improvements, in terms of reducing the number of hospital admissions, in favour of the intervention group. At baseline, patients were taking, on average, 7.4 drugs in both the intervention and the control groups. At follow-up, the weighted mean number of drugs was reduced (-0.2) in the intervention group but increased (+0.2) in controls.

Conclusions: There is no convincing evidence that the strategies assessed in the present review are effective in reducing polypharmacy or have an impact on clinically relevant endpoints. Interventions are complex; it is still unclear how best to organize and implement them to achieve a reduction in inappropriate polypharmacy. There is therefore a need to develop more effective strategies to reduce inappropriate polypharmacy and to test them in large, pragmatic randomized controlled trials on effectiveness and feasibility.

Keywords: aged; hospitalisation; medication therapy management; meta-analysis; mortality; polypharmacy.

Figure 1

Study selection process [Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) flow diagram]

Figure 2

Data and analysis on all‐cause mortality during the study period, using binary random effects and the DerSimonian‐Laird method. CI, confidence interval; Ctrl, control; Ev, event; Trt, treatment/intervention

Figure 3

Data and analysis on all‐cause mortality during the study period (only randomized controlled trials and cluster randomized controlled trials), binary random effects and the DerSimonian‐Laird method. CI, confidence interval; Ctrl, control; Ev, event; Trt, treatment/intervention

Figure 4

Subgroup analysis on all‐cause mortality during the study period including only studies with short follow‐ups (2–6 months), binary random effects and the DerSimonian‐Laird method. CI, confidence interval; Ctrl, control; Ev, event; Trt, treatment/intervention

Figure 5

Subgroup analysis on all‐cause mortality during study period including only studies with long follow‐ups (12–18 months), binary random effects and the DerSimonian‐Laird method. CI, confidence interval; Ctrl, control; Ev, event; Trt, treatment/intervention

Figure 6

Quality assessments: the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. CI, confidence interval; cRCT, cluster RCT; OR, odds ratio; RCT, randomized controlled trial; RR, relative risk. CI confidence interval; RR Risk ratio; OR Odds ratio. *Twelve RCTs, four cRCT, and two non‐randomized controlled intervention studies. †The quality of evidence is downgraded by imprecise results, small number of events and wide confidence interval. An appropriate random sequence generation was used in eight. Allocation concealment was adequate in six studies. Seven studies defined mortality as an outcome measure, all other studies reported on mortality as lost to follow‐up. ‡One cRCT. §The quality of evidence is downgraded by imprecise results, small number of events and wide confidence interval. Allocation concealment was unclear. Lack of blinding of participants, professionals and outcome assessors. A per protocol analysis was performed. ¶Clinical and methodology heterogeneity exist – too dissimilar; does not make sense to pool statistically. **Three RCTs, one cRCT, and one non‐randomized controlled intervention study. ††The quality of evidence is downgraded by imprecise results, small number of events and wide confidence interval. Randomisation process unclear. Lack of blinding of participants, professionals and outcome assessors. Only one study used an intent‐to‐treat analysis. ‡‡Two RCTs. §§The quality of evidence is downgraded by imprecise results, small number of events and wide confidence interval. Unclear allocation concealment. High risk of contamination bias. An intent‐to‐treat analysis was performed in one study. ¶¶One multicentre RCT (data from Sturgess et al. 2003 is included in this trial). ***The quality of evidence is downgraded by study limitations. Unclear how randomisation was performed. Outcome assessors were not blinded. A per‐protocol analysis was performed. Lack of information regarding patient selection. †††One RCT. ‡‡‡The quality of evidence is downgraded by imprecise results, small number of events and wide confidence interval. A per protocol analysis was performed. No power calculation. Allocation concealment and blinding of outcome assessment unclear. §§§Two RCTs and one cRCT. ¶¶¶The quality of evidence is downgraded by imprecise results, small number of events and wide confidence interval. Allocation concealment was unclear. Lack of blinding of participants, professionals and outcome assessors. A per protocol analysis was performed in two studies. Important baseline differences in one study. ****Studies do not provide information on means with standard deviations. Not possible to pool data