Evidence map›Paper›PMID 42900434›Full record

ArticleInternational journal of clinical pharmacy2026

Development, implementation and evaluation of a sustainable medication-use process in the intensive care unit: a lean-based quality improvement study.

Rou Qing Chen, Shirley Xie, Tim Frenzel, Sanne Percic-van Doorne, Bart van den Bemt, Stephanie Natsch, Charlotte Bekker

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Article in International journal of clinical pharmacy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Rou Qing Chen *Department of Pharmacy, Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Centre, Nijmegen, The Netherlands.
Shirley Xie *Department of Pharmacy, Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Centre, Nijmegen, The Netherlands.
Tim FrenzelDepartment of Intensive Care, Radboud Institute for Health Sciences, Radboud University Medical Centre, Nijmegen, The Netherlands.
Sanne Percic-van DoorneDepartment of Intensive Care, Radboud Institute for Health Sciences, Radboud University Medical Centre, Nijmegen, The Netherlands.
Bart van den BemtDepartment of Pharmacy, Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Centre, Nijmegen, The Netherlands.
Stephanie NatschDepartment of Pharmacy, Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Centre, Nijmegen, The Netherlands.
Charlotte BekkerDepartment of Pharmacy, Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Centre, Nijmegen, The Netherlands. Charlotte.Bekker@radboudumc.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the Intensive Care Unit (ICU), substantial quantities of medication are wasted, negatively affecting ecological and economic sustainability.

aimThis study aimed to develop, implement, and evaluate an ecologically and economically sustainable medication-use process to reduce medication waste in the ICU of a Dutch academic hospital.

methodThis lean-based quality improvement study comprised three phases: (I) Three-week baseline medication waste assessment in terms of quantity (i.e., disposed medication units) and economic value per 100 ICU beds per day. (II) Development and implementation of a sustainable medication-use process using lean principles. Causes of medication waste were identified among hospital staff using qualitative methods, and targeted interventions were identified and implemented accordingly. (III) Post-implementation effect evaluation of the sustainable medication-use process on medication waste.

resultsAt baseline, a mean total of 113 units, worth €1037, were wasted daily per 100 ICU beds. Causes for medication waste were: insufficient knowledge among hospital staff about quantities and impacts of medication waste; suboptimal medication ordering, supplying and preparing, resulting in unnecessary medication waste; and patient's therapy changes/discontinuation. Interventions implemented were: awareness campaigns on medication waste; adjustment of protocols and work processes to prevent excess order, supply and preparation of medication; and dispensing individually labelled medication to the patient following transfer or discharge. Implementing these interventions reduced medication waste by 31.8% to 77 units per 100 ICU beds per day, and economic losses decreased by 18.4% to €846.

conclusionImplementation of a sustainable medication-use process targeting staff's knowledge and work processes, reduced the extent of wasted medications in the ICU and associated costs.

Indexed as

Intensive care unitsMedical waste disposalMedication systems, hospitalSustainable developmentTotal quality management

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.