In older inpatients with polypharmacy, medication optimization did not improve outcomes at 48 wk

Abstract

Question

In older inpatients with polypharmacy, does multidisciplinary, team-based medication optimization improve clinical outcomes?

Design

Randomized controlled trial (RCT).

Blinding

Treatment allocation concealed; blinded (data collectors).^*

Setting

8 internal medicine wards in a community hospital in Japan.

Patients

460 inpatients aged ≥65 years (mean age, 82 y; 51% women; median of 8 regular medications) who were receiving ≥5 regular medications (any orally administered prescription medication documented in the patient’s medical record with duration ≥28 d at the time of admission, excluding as-needed medications), and with expected hospitalization of ≥1 week. Key exclusions: life expectancy <1 month or physician’s disagreement with patient’s participation.

Interventions

Multidisciplinary, team-based medication optimization initiated within 48 hours of random assignment (n = 229) or usual care (n = 231). In the optimization group, a multidisciplinary deprescribing team (a physician and a pharmacist) used patient data and a trial-specific clinical decision-support system to create a list of potentially inappropriate prescriptions and prescribing omissions. The list was reviewed by the team who followed a predefined algorithm and considered medication indications, balance of benefits and harms, and separate evaluation of symptomatic and preventive medications. The review was discussed with patients and/or families and, with consent, the medication optimization plan was recommended to the attending physician who could accept or decline the proposal. The summary was also shared with patients’ primary care physicians and community pharmacists at discharge. Usual care comprised medication reconciliation at admission by ward-based pharmacists.

Commentary

Polypharmacy is common among older adults and increases the risk for medically treated falls, emergency department visits, hospitalizations, and other adverse drug events (1). Intentional deprescribing interventions have the potential to reduce preventable medication-associated harms, but evidence has been mixed (2).

The RCTs by Ie and colleagues and Phelan and colleagues assessed the effects of novel deprescribing interventions using targeted, team-based medication optimization and prescriber clinical decision support paired with patient education in older adults. Neither trial found that the intervention reduced patient-centered outcomes, including medically treated falls, unscheduled hospitalizations, and mortality.

Although these trials did not show statistically significant improvements in their primary outcomes with deprescribing, both showed benefit in some secondary outcomes that should temper cynicism for deprescribing efforts in older adults (3). In the trial by Ie and colleagues, the intervention group was prescribed 0.62 fewer medications (95% CI, 0.03 to 1.20) and fewer patients were prescribed ≥1 potentially inappropriate medication compared with the control group at 12 months. Similarly, the intervention used by Phelan and colleagues increased the likelihood of discontinuation of tricyclic antidepressants compared with control at 6 months. Notably, this intervention did not lead to discontinuation of benzodiazepines, opioids, or other central nervous system depressants targeted by the intervention. Although some reductions in medication use were achieved, most clinicians would not consider these to be clinically important reductions in the quantity of medications used, which is pertinent because the absolute number of concurrent medication exposures is the single most important predictor of adverse drug events for older adults with polypharmacy (4).

Greater focus should be placed on the development and evaluation of effective and generalizable deprescribing strategies. A comprehensive assessment of the intervention itself, including pragmatic measures, such as its reach into the target population and clinician adoption of the proposed initiative, will help identify whether a lack of effectiveness is due to the design or implementation of the health promotion intervention (5). In the meantime, deprescribing initiatives remain an important component of the multimodal approach to reduce medication-associated harms in older adults, even if the best path to achieve it is unclear.

Results: Multidisciplinary team-based medication optimization vs. usual care in older inpatients with polypharmacy (modified intention-to-treat analysis)^†

Outcomes	Event Rates		HR/RR (95% CI) at 48 wk
	Optimization‡	Usual care‡
All-cause death, unscheduled hospital visits, or rehospitalization	49%	52%	HR 0.98 (0.75 to 1.27)§
Adverse events	57%	60%	RR 0.96 (0.82 to 1.13)||
Falls and fall-related injuries			HR 0.86 (0.56 to 1.32)
All-cause mortality			HR 1.00 (0.68 to 1.47)
Unscheduled hospital visits			HR 0.96 (0.70 to 1.32)
Rehospitalizations			HR 0.92 (0.64 to 1.33)

HR = hazard ratio; RR = relative risk; CI defined in Glossary. Primary outcome indicated by boldface.

^†Included 442 patients who were randomly assigned and were not found to be ineligible after enrollment.

^‡Deprescribing recommendations were made for 188 patients and ≥1 proposal was accepted for 153 (81%) patients and 69% of proposals in the Optimization group. The optimization group had fewer prescriptions for potentially inappropriate medications than the usual care group at discharge (26% vs. 33%; mean difference, 0.56 [CI, 0.33 to 0.94]) and at 6 (28% vs. 38%; mean difference, 0.50 [CI, 0.29 to 0.86]) and 12 mo (27% vs. 37%; mean difference, 0.45 [CI, 0.25 to 0.80]).

^§500 patients were needed to detect a 35% rate of the primary composite outcome in the optimization group vs. 40% in the usual care group (80% power, 2-sided α = 0.05, assumed 15% withdrawal rate).

^||RR and CI calculated from event rates in article.