Intervention on Look-alike Sound-alike Medication Errors for Patient Safety in Healthcare Institutions: a Systematic Review
Year: 2025
Type: preprint
Study design: Systematic Review
Abstract: Globally, Look-Alike Sound-Alike (LASA) medication errors have been reported to cause patient harm and death. There are different interventions to prevent or reduce these errors. Most notable is the Tall Man Lettering (TML), which has received enormous attention, while the other interventions are less well-known. Therefore, this systematic review sought to compare the effectiveness of other alternative interventions with the TML. Four (4) databases including, CINAHL Plus, EMBASE via Ovid, PsycINFO via Ovid, and Scopus, were searched for studies that focused on interventions on LASA medications. Searches were done between January and April 2025. Covidence was employed for managing the review. The review protocol was registered with PROSPERO, with an ID CRD42025642094. Fifteen (15) studies were identified as eligible for review. All interventions were categorized into text enhancement (including TML), pre-approval detection of confusable drug names by regulatory bodies, a machine learning based clinical decision support system, prevention by drug indication, and an algorithmic approach for improving auditory perception of drug names. The TML shows varying effectiveness, ranging from less to more effective, based on outcome indicators measured compared to other text enhancement interventions. Comparison could not be made with other interventions that are not text enhancement. The TML cannot be outrightly declared as being more effective because of the varying effectiveness range during comparable comparisons. It is recommended that a combination of interventions will be more effective in drastically preventing and/or reducing LASA medication errors.
Authors: Oyebode Oluwaseyi Dosunmu, Rasaq Adisa
Institutions: University of Edinburgh, University of Ibadan
Language: English
Subfield: Emergency Medical Services
Field: Health Professions
Domain: Health Sciences
Open Access status: gold
OpenAlex ID: W4413885264
