• Dtsch. Med. Wochenschr. · Nov 2023

    [Scoring tool to identify patients at increased risk for drug-related problems: results of a point prevalence study at hospital admission].

    • Saskia Berger, Heike Hilgarth, Andreas Fischer, Yvonne Remane, Jochen Schmitt, and Holger Knoth.
    • Klinik-Apotheke, Universitätsklinikum Carl Gustav Carus der Technischen Universität Dresden.
    • Dtsch. Med. Wochenschr. 2023 Nov 1; 148 (23): e113e119e113-e119.

    IntroductionDrug therapy is a high-risk process and requires special attention, especially at sectoral borders. Pharmaceutical services such as medication review are appropriate measures to identify drug-related problems and thus improve the safety of drug therapy. Risk-scoring tools have been described in the literature as helpful for prioritizing medication reviews for patients at high risk for drug-related problems.MethodsIn a multi-centre point prevalence study, we identified patients at increased risk for medication-related problems at hospital admission using the medication risk tool. In addition, the current level of implementation of pharmacy services was surveyed.ResultsA total of 11 (58%; 11/19) hospital pharmacies in Saxony participated in the point prevalence survey. The scoring tool identified 32% (279/875) of patients at increased risk for medication-related problems (Meris score >12 group) at admission. Thereby, the number of drugs in the Meris score >12 group was 10.6 (average; standard deviation 3.5; n=279), while in the Meris score ≤12 group it was only five drugs per patient (average 4.6; standard deviation 2.8; n=596). The age of patients in the Meris score >12 group averaged 75.9 ± 11 years, while the age of patients in the Meris score ≤12 group averaged 60.6 ± 17.9 years.DiscussionPrioritization with the help of a risk-scoring tool is essential as pharmacy services in Saxon hospitals still need to be regularly established and in order to identify patients with an increased risk for drug-related problems at an early stage.The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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