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The effect of computerised decision support alerts tailored to intensive care on the administration of high-risk drug combinations, and their monitoring: a cluster randomised stepped-wedge trial.
Bakker, Tinka; Klopotowska, Joanna E; Dongelmans, Dave A; Eslami, Saeid; Vermeijden, Wytze J; Hendriks, Stefaan; Ten Cate, Julia; Karakus, Attila; Purmer, Ilse M; van Bree, Sjoerd H W; Spronk, Peter E; Hoeksema, Martijn; de Jonge, Evert; de Keizer, Nicolette F; Abu-Hanna, Ameen.
Afiliación
  • Bakker T; Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Methodology, Amsterdam Public Health, Amsterdam, Netherlands. Electronic address: t.bakker1@amsterdamumc.nl.
  • Klopotowska JE; Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Digital Health, Amsterdam Public Health, Amsterdam, Netherlands.
  • Dongelmans DA; Department of Intensive Care Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Quality of Care, Amsterdam Public Health, Amsterdam, Netherlands.
  • Eslami S; Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Pharmaceutical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Vermeijden WJ; Department of Intensive Care, Medisch Spectrum Twente, Enschede, Netherlands.
  • Hendriks S; Department of Intensive Care, Albert Schweitzer Ziekenhuis, Dordrecht, Netherlands.
  • Ten Cate J; Department of Intensive Care, The Netherlands Cancer Institute, Amsterdam, Netherlands.
  • Karakus A; Department of Intensive Care Diakonessenhuis Utrecht, Utrecht, Netherlands.
  • Purmer IM; Department of Intensive Care, Haga Hospital, The Hague, Netherlands.
  • van Bree SHW; Department of Intensive Care, Ziekenhuis Gelderse Vallei, Ede, Netherlands.
  • Spronk PE; Department of Intensive Care Medicine, Gelre Hospitals, Apeldoorn, Netherlands.
  • Hoeksema M; Zaans Medisch Centrum, Department of Anesthesiology, Intensive Care and Pain Management, Zaandam, Netherlands.
  • de Jonge E; Department of Intensive Care, Leiden University Medical Center, Leiden, Netherlands.
  • de Keizer NF; Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Quality of Care, Amsterdam Public Health, Amsterdam, Netherlands.
  • Abu-Hanna A; Department of Medical Informatics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Methodology, Amsterdam Public Health, Amsterdam, Netherlands.
Lancet ; 403(10425): 439-449, 2024 Feb 03.
Article en En | MEDLINE | ID: mdl-38262430
ABSTRACT

BACKGROUND:

Drug-drug interactions (DDIs) can harm patients admitted to the intensive care unit (ICU). Yet, clinical decision support systems (CDSSs) aimed at helping physicians prevent DDIs are plagued by low-yield alerts, causing alert fatigue and compromising patient safety. The aim of this multicentre study was to evaluate the effect of tailoring potential DDI alerts to the ICU setting on the frequency of administered high-risk drug combinations.

METHODS:

We implemented a cluster randomised stepped-wedge trial in nine ICUs in the Netherlands. Five ICUs already used potential DDI alerts. Patients aged 18 years or older admitted to the ICU with at least two drugs administered were included. Our intervention was an adapted CDSS, only providing alerts for potential DDIs considered as high risk. The intervention was delivered at the ICU level and targeted physicians. We hypothesised that showing only relevant alerts would improve CDSS effectiveness and lead to a decreased number of administered high-risk drug combinations. The order in which the intervention was implemented in the ICUs was randomised by an independent researcher. The primary outcome was the number of administered high-risk drug combinations per 1000 drug administrations per patient and was assessed in all included patients. This trial was registered in the Netherlands Trial Register (identifier NL6762) on Nov 26, 2018, and is now closed.

FINDINGS:

In total, 10 423 patients admitted to the ICU between Sept 1, 2018, and Sept 1, 2019, were assessed and 9887 patients were included. The mean number of administered high-risk drug combinations per 1000 drug administrations per patient was 26·2 (SD 53·4) in the intervention group (n=5534), compared with 35·6 (65·0) in the control group (n=4353). Tailoring potential DDI alerts to the ICU led to a 12% decrease (95% CI 5-18%; p=0·0008) in the number of administered high-risk drug combinations per 1000 drug administrations per patient, after adjusting for clustering and prognostic factors.

INTERPRETATION:

This cluster randomised stepped-wedge trial showed that tailoring potential DDI alerts to the ICU setting significantly reduced the number of administered high-risk drug combinations. Our list of high-risk drug combinations can be used in other ICUs, and our strategy of tailoring alerts based on clinical relevance could be applied to other clinical settings.

FUNDING:

ZonMw.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Eritrodermia Ictiosiforme Congénita / Sistemas de Apoyo a Decisiones Clínicas / Cuidados Críticos / Errores Innatos del Metabolismo Lipídico / Enfermedades Musculares Tipo de estudio: Clinical_trials / Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Adolescent / Adult / Humans Idioma: En Revista: Lancet Año: 2024 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Eritrodermia Ictiosiforme Congénita / Sistemas de Apoyo a Decisiones Clínicas / Cuidados Críticos / Errores Innatos del Metabolismo Lipídico / Enfermedades Musculares Tipo de estudio: Clinical_trials / Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Adolescent / Adult / Humans Idioma: En Revista: Lancet Año: 2024 Tipo del documento: Article Pais de publicación: Reino Unido