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Τρίτη 30 Ιανουαρίου 2018

Computerised decision to reduce inappropriate medication in the elderly: a systematic review with meta-analysis protocol

Introduction

Life expectancy continues to increase in developed countries. Elderly people are more likely to consume more medications and become vulnerable to age-related changes in drugs' pharmacokinetics and pharmacodynamics. Recent studies have identified opportunities and barriers for deprescribing potentially inappropriate medications. It has already been demonstrated that computerised decision support systems can reduce physician orders for unnecessary tests. We will systematically review the available literature to understand if computerised decision support is effective in reducing the use of potentially inappropriate medications, thus having an impact on health outcomes.

Methods and analysis

A systematic review will be conducted using MEDLINE, CENTRAL, EMBASE and Web of Science databases, as well as the grey literature assessing the effectiveness of computer decision support interventions in deprescribing inappropriate medication, with an impact on health outcomes in the elderly. The search will be performed during January and February 2018. Two reviewers will conduct articles' screening, selection and data extraction, independently and blind to each other. Eligible sources will be selected after discussing non-conformities. All extracted data from the included articles will be assessed based on studies' participants, design and setting, methodological quality, bias and any other potential sources of heterogeneity. This review will be conducted and reported in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement of quality for reporting systematic reviews and meta-analyses.

Ethics and dissemination

As a systematic review, this research is exempt from ethical approval. We intend to publish the full article in a related peer-reviewed journal and present it at international conferences.

PROSPEROregistration number

CRD42017067021.



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