Robot-assisted medication management in home care and long-term care settings: a mixed-method systematic review

Abstract

INTRODUCTION: Medication errors and non-adherence in older adults are major issues linked to polypharmacy, cognitive decline, and caregiver burden. Medication management robots offer promise in improving patient care but require thorough evaluation . This review synthesizes the experiences of patients and caregivers, assesses the effectiveness of MMR in enhancing medication safety and minimizing errors, and offers insights into its broader implications for elderly home care. METHODS: A mixed-methods systematic review was conducted using PRISMA guidelines. Searches were performed across six databases - PubMed, Scopus, Web of Science, Embase, CINAHL, and ProQuest - without publication date limits. Studies were appraised using the Mixed Methods Appraisal Tool (MMAT), and findings were synthesized through a convergent approach. RESULTS: Six studies (3 qualitative, 2 quantitative, 1 mixed-methods) from Sweden, Finland, and the U.S.A. were included. MMRs improved adherence, reduced medication errors, enhanced coordination among healthcare providers, and supported patient autonomy. Key challenges involved technical issues, such as incompatibility with liquid medications, concerns about privacy, and reluctance from users due to diminished human contact. CONCLUSION: MMRs show promise in elderly care, but successful adoption depends on structured training, ethical safeguards, and user-centered design. Further research is required to validate their long-term impact and optimize implementation strategies. REGISTRATION: The protocol for this review was registered with PROSPERO (registration number: CRD42024611310): https://www.crd.york.ac.uk/PROSPERO/view/CRD42024611310.

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