Development and validation of a clinical decision support system to prevent anticoagulant duplications.

Anticoagulants Clinical decision support system (CDSS) Duplicate prescribing Electronic prescribing Medication errors Patient safety

Journal

International journal of medical informatics
ISSN: 1872-8243
Titre abrégé: Int J Med Inform
Pays: Ireland
ID NLM: 9711057

Informations de publication

Date de publication:
07 Apr 2024
Historique:
received: 15 02 2024
revised: 28 03 2024
accepted: 04 04 2024
medline: 26 4 2024
pubmed: 26 4 2024
entrez: 26 4 2024
Statut: aheadofprint

Résumé

Unintended duplicate prescriptions of anticoagulants increase the risk of serious adverse events. Clinical Decision Support Systems (CDSSs) can help prevent such medication errors; however, sophisticated algorithms are needed to avoid alert fatigue. This article describes the steps taken in our hospital to develop a CDSS to prevent anticoagulant duplication (AD). The project was composed of three phases. In phase I, the status quo was established. In phase II, a clinical pharmacist developed an algorithm to detect ADs using daily data exports. In phase III, the algorithm was integrated into the hospital's electronic health record system. Alerts were reviewed by clinical pharmacists before being sent to the prescribing physician. We conducted a retrospective analysis of all three phases to assess the impact of the interventions on the occurrence and duration of ADs. Phase III was analyzed in more detail regarding the acceptance rate, sensitivity, and specificity of the alerts. We identified 91 ADs in 1581 patients receiving two or more anticoagulants during phase I, 70 ADs in 1692 patients in phase II, and 57 ADs in 1575 patients in phase III. Mean durations of ADs were 1.8, 1.4, and 1.1 calendar days during phases I, II, and III, respectively. In comparison to the baseline in phase I, the relative risk reduction of AD in patients treated with at least two different anticoagulants during phase III was 42% (RR: 0.58, CI: 0.42-0.81). A total of 429 alerts were generated during phase III, many of which were self-limiting, and 186 alerts were sent to the respective prescribing physician. The acceptance rate was high at 97%. We calculated a sensitivity of 87.4% and a specificity of 87.9%. The stepwise development of a CDSS for the detection of AD markedly reduced the frequency and duration of medication errors in our hospital, thereby improving patient safety.

Sections du résumé

BACKGROUND AND OBJECTIVE OBJECTIVE
Unintended duplicate prescriptions of anticoagulants increase the risk of serious adverse events. Clinical Decision Support Systems (CDSSs) can help prevent such medication errors; however, sophisticated algorithms are needed to avoid alert fatigue. This article describes the steps taken in our hospital to develop a CDSS to prevent anticoagulant duplication (AD).
METHODS METHODS
The project was composed of three phases. In phase I, the status quo was established. In phase II, a clinical pharmacist developed an algorithm to detect ADs using daily data exports. In phase III, the algorithm was integrated into the hospital's electronic health record system. Alerts were reviewed by clinical pharmacists before being sent to the prescribing physician. We conducted a retrospective analysis of all three phases to assess the impact of the interventions on the occurrence and duration of ADs. Phase III was analyzed in more detail regarding the acceptance rate, sensitivity, and specificity of the alerts.
RESULTS RESULTS
We identified 91 ADs in 1581 patients receiving two or more anticoagulants during phase I, 70 ADs in 1692 patients in phase II, and 57 ADs in 1575 patients in phase III. Mean durations of ADs were 1.8, 1.4, and 1.1 calendar days during phases I, II, and III, respectively. In comparison to the baseline in phase I, the relative risk reduction of AD in patients treated with at least two different anticoagulants during phase III was 42% (RR: 0.58, CI: 0.42-0.81). A total of 429 alerts were generated during phase III, many of which were self-limiting, and 186 alerts were sent to the respective prescribing physician. The acceptance rate was high at 97%. We calculated a sensitivity of 87.4% and a specificity of 87.9%.
CONCLUSION CONCLUSIONS
The stepwise development of a CDSS for the detection of AD markedly reduced the frequency and duration of medication errors in our hospital, thereby improving patient safety.

Identifiants

pubmed: 38669733
pii: S1386-5056(24)00109-6
doi: 10.1016/j.ijmedinf.2024.105446
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

105446

Informations de copyright

Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Hendrike Dahmke (H)

Hospital Pharmacy, Kantonsspital Aarau, 5000 Aarau, Switzerland. Electronic address: hendrike.dahmke@ksa.ch.

Francisco Cabrera-Diaz (F)

Hospital Pharmacy, General University Hospital of Ciudad Real, 13005 Ciudad Real, Spain.

Marc Heizmann (M)

Division of Oncology, Haematology and Transfusion Medicine, Kantonsspital Aarau, Aarau, Switzerland.

Sophie Stoop (S)

Department of Chemistry and Applied Biosciences, Eidgenossische Technische Hochschule Zürich, Zurich, Switzerland.

Philipp Schuetz (P)

Department of Internal Medicine, Kantonsspital Aarau, 5000 Aarau, Switzerland.

Rico Fiumefreddo (R)

Department of Internal Medicine, Kantonsspital Aarau, 5000 Aarau, Switzerland.

Claudia Zaugg (C)

Hospital Pharmacy, Kantonsspital Aarau, 5000 Aarau, Switzerland.

Classifications MeSH