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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Interventions to enhance medication therapy safety in older patients with cognitive impairment-protocol of a
Viktoria Jungreithmayr1, Theresa Terstegen1, Annette Eidam2
1Heidelberg University, Medical Faculty Heidelberg / Heidelberg University Hospital, Internal Medicine IX - Department of Clinical Pharmacology and Pharmacoepidemiology, Cooperation Unit Clinical Pharmacy, Heidelberg, Germany.
Introduction:
Cognitive impairment is considered a challenge in medication management for both the affected patient as well as their caregiver. Numerous studies have investigated interventions aiming to improve medication therapy safety in this population; however, there is insufficient knowledge on interventions which support patients and caregivers effectively. The aim of this systematic review is to (1) identify interventions to improve medication therapy safety in older patients with cognitive impairment, and (2) to evaluate their effectiveness.
Methods And Analysis:
We will conduct a systematic review of literature with participatory elements of public involvement in every step of the process. Five literature databases (PubMed, CENTRAL, Embase, PsycINFO and CINAHL) will be screened to identify interventions to improve medication therapy safety in older (≥65 years of age) adults with cognitive impairment. To support methodology and evidence synthesis, we will conduct expert panel discussions as well as focus group discussions of caregivers and healthcare professionals. Study selection, data extraction and bias assessment will be conducted independently by two reviewers. For data synthesis, studies will be organised by setting (eg, community setting, hospital setting, nursing home setting).
Ethics And Dissemination:
The responsible Ethics Committee of the Medical Faculty of Heidelberg granted approval for the public involvement strategies in this project (S-562/2024). Results will be presented by publication in an academic journal and at scientific conferences.
Prospero Registration Number:
CRD42024623352.
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