Impact on process results of clinical decision support systems (CDSSs) applied to medication use: overview of systematic reviews

Keywords: Decision Support Systems, Clinical, Technology Assessment, Biomedical, Review [Publication Type].

Abstract

Objective: The purpose of this overview (systematic review of systematic reviews) is to evaluate the impact of clinical decision support systems (CDSS) applied to medication use in the care process.

Methods: A search for systematic reviews that address CDSS was performed on Medline following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Cochrane recommendations. Terms related to CDSS and systematic reviews were used in combination with Boolean operators and search field tags to build the electronic search strategy. There was no limitation of date or language for inclusion. We included revisions that investigated, as a main or secondary objective, changes in process outcomes. The Revised Assessment of Multiple Systematic Reviews (R-AMSTAR) score was used to evaluate the quality of the studies.

Results: The search retrieved 954 articles. Five articles were added through manual search, totaling an initial sample of 959 articles. After screening and reading in full, 44 systematic reviews met the inclusion criteria. In the medication-use processes where CDSS was used, the most common stages were prescribing (n=38 (86.36%) and administering (n=12 (27.27%)). Most of the systematic reviews demonstrated improvement in the health care process (30/44 – 68.2%). The main positive results were related to improvement of the quality of prescription by the physicians (14/30 – 46.6%) and reduction of errors in prescribing (5/30 - 16.6%). However, the quality of the studies was poor, according to the score used.

Conclusion: CDSSs represent a promising technology to optimize the medication-use process, especially related to improvement in the quality of prescriptions and reduction of prescribing errors, although higher quality studies are needed to establish the predictors of success in these systems.

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Published
2017-12-18
Section
Original Research

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