MITIGATING MEDICATION MISHAPS: GOOD CLINICAL PRACTICES FOR LOOK-ALIKE, SOUND-ALIKE DRUG MANAGEMENT
Pdf
European Statement
Patient Safety and Quality Assurance
Author(s)
Öznur Gülertürk Er (1), Aslı Kamburoglu (2), Cumhur Yetmez (3), Ülker Şener (4), Aslı Özyıldırım (5)
Why was it done?
Look-Alike/Sound-Alike (LASA) medications are those that share similar appearances or phonetic characteristics when written or spoken. Such similarities can lead to confusion among healthcare professionals and may result in medication errors that can adversely affect patients (1).
What was done?
The primary objective of this study is to systematically evaluate medication names that exhibit similarities in appearance and sound, specifically focusing on the medications listed in the hospital’s formulary. Our goal is to minimize medication errors by accurately identifying real or potential risks associated with Look-Alike/Sound-Alike (LASA) drugs.
How was it done?
An algorithm utilizing Bigram Similarity (BI-SIM) was employed to calculate the orthographic and/or phonetic similarities of drug names listed in the hospital’s formulary. A total of 9,253 drug names were evaluated, excluding enteral nutrition products, cosmetics, and food supplements. The remaining 5,214 drug names were scored based on the BI-SIM algorithm. Drug pairs exhibiting a similarity ratio of 0.5 or higher were included in the study, resulting in 345 pairs. The clinical risks associated with these drug pairs—considering factors such as route of administration, potency, and pharmaceutical dosage form similarities—were scored and aggregated according to their BI-SIM similarity scores. Ultimately, these total similarity scores were placed within a risk matrix assessing the potential harm to patients in the event of a medication error. A list comprising 30 pairs of high- and very-high-risk drugs was generated. Medications on this list were presented using mid Tall Man font and labeled with cautionary notices (2).
What has been achieved?
We improved our hospital formulary by using a special, non-interpretive, analytical and repeatable algorithm.
What next?
The perception of healthcare professionals regarding the similarity assessments of drug pairs in the new LASA drug list, which we created using the similarity algorithm and risk matrix, will be evaluated.