Abstract

Scalable deprescribing interventions may reduce polypharmacy and the use of potentially inappropriate medications (PIMs); however, few studies have been large enough to evaluate the impact that deprescribing may have on adverse drug events (ADEs). To evaluate the effect of an electronic deprescribing decision support tool on ADEs after hospital discharge among older adults with polypharmacy. This was a cluster randomized clinical trial of older (≥65 years) hospitalized patients with an expected survival of more than 3 months who were admitted to 1 of 11 acute care hospitals in Canada from August 22, 2017, to January 13, 2020. At admission, participants were taking 5 or more medications per day. Data analyses were performed from January 3, 2021, to September 23, 2021. Personalized reports of deprescribing opportunities generated by MedSafer software to address usual home medications and measures of prognosis and frailty. Deprescribing reports provided to the treating team were compared with usual care (medication reconciliation). The primary outcome was a reduction of ADEs within the first 30 days postdischarge (including adverse drug withdrawal events) captured through structured telephone surveys and adjudicated blinded to intervention status. Secondary outcomes were the proportion of patients with 1 or more PIMs deprescribed at discharge and the proportion of patients with an adverse drug withdrawal event (ADWE). A total of 5698 participants (median [range] age, 78 [72-85] years; 2858 [50.2%] women; race and ethnicity data were not collected) were enrolled in 3 clusters and were adjudicated for the primary outcome (control, 3204; intervention, 2494). Despite cluster randomization, there were group imbalances, eg, the participants in the intervention arm were older and had more PIMS prescribed at baseline. After hospital discharge, 4989 (87.6%) participants completed an ADE interview. There was no significant difference in ADEs within 30 days of discharge (138 [5.0%] of 2742 control vs 111 [4.9%] of 2247 intervention participants; adjusted risk difference [aRD] -0.8%; 95% CI, -2.9% to 1.3%). Deprescribing increased from 795 (29.8%) of 2667 control to 1249 (55.4%) of 2256 intervention participants [aRD, 22.2%; 95% CI, 16.9% to 27.4%]. There was no difference in ADWEs between groups. Several post hoc sensitivity analyses, including the use of a nonparametric test to address the low cluster number, group imbalances, and potential biases, did not alter study conclusions. This cluster randomized clinical trial showed that providing deprescribing clinical decision support during acute hospitalization had no demonstrable impact on ADEs, although the intervention was safe and led to improvements in deprescribing. ClinicalTrials.gov Identifier: NCT03272607.

Highlights

  • IMPORTANCE Scalable deprescribing interventions may reduce polypharmacy and the use of potentially inappropriate medications (PIMs); few studies have been large enough to evaluate the impact that deprescribing may have on adverse drug events (ADEs)

  • There were group imbalances, eg, the participants in the intervention arm were older and had more PIMS prescribed at baseline

  • There was no significant difference in ADEs within 30 days of discharge (138 [5.0%] of 2742 control vs 111 [4.9%] of 2247 intervention participants; adjusted risk difference [Adjusted risk differences (aRD)] −0.8%; 95% CI, −2.9% to 1.3%)

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Summary

Methods

We evaluated the use of MedSafer using a cluster randomized trial at 11 participating acute care hospitals in Canada. All hospital sites obtained study approvals from their local research ethics board and administration. Eligible patients were approached for their consent to the 30-day postdischarge telephone interview; a family member or proxy granted consent for patients lacking capacity, in accordance with the ethics regulations of Canada.[18] The trial protocol and statistical analysis plan are available in Supplement 1. The study followed Consolidated Standards of Reporting Trials (CONSORT) reporting guidelines extension for cluster randomized trials.[19]

Results
Discussion
Conclusion
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