Pharmacist-Led Medication Reconciliation to Reduce Polypharmacy Risk in Elderly Outpatients
DOI:
https://doi.org/10.5281/zenodo.22849398Keywords:
medication reconciliation, polypharmacy, deprescribing, potentially inappropriate medications, clinical pharmacy servicesAbstract
Polypharmacy is close to the modal experience of ageing in health systems where chronic-disease guidelines accumulate additively across an increasingly multimorbid older population, and the resulting medication lists are a leading, well-documented source of preventable emergency hospitalizations in older adults. Pharmacist-led medication reconciliation -- the structured comparison of a patient's actual regimen against the documented record at each transition of care, followed by resolution of the discrepancies found -- has been proposed and trialed across hospital, community, and ambulatory settings as a response. This article synthesizes that literature: the scope and mechanisms of polypharmacy-related harm; the structure of reconciliation as a multi-step process rather than a single documentation act; the explicit criteria-based tools, including STOPP/START, the Beers Criteria, and their frailty- and anticholinergic-burden-specific variants, that operationalize potentially inappropriate prescribing so it can be screened for systematically; the pharmacist-led intervention models trialed at hospital admission, hospital discharge, in the community, and in dedicated ambulatory clinics; and deprescribing as the structured extension of reconciliation once an appropriateness judgment has been made. Read together, the evidence is genuinely consistent that pharmacist-led reconciliation and review improve process measures -- discrepancy resolution, prescribing appropriateness, and total medication burden -- while the evidence for consistent reductions in hospital readmission or mortality is considerably more mixed, with well-designed trials on both sides of that question. We treat that gap as an honest feature of the evidence base rather than a problem to explain away, and close with the workforce, generalizability, and intervention-heterogeneity challenges that remain open.
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