Sound-Alike Look-Alike Confusion and Matching Medication Product Attributes: Simulated Case-Control Studies

Abstract

Background: Sound-alike look-alike (SALA) medication confusions harm as many as 250 000 Americans annually. Most preventive strategies focus on medication name similarities. Objectives: To evaluate the association between matching medication product attributes and SALA confusion. Methods: We simulated 20 000 case-control studies using the Institute for Safe Medication Practices’ List of Confused Drug Names as case pairs and 4 randomly selected control pairs per case pair from the First DataBank MedKnowledge (FDBM) database. We extracted 7 product attributes for each medication from the FDBM database. We used logistic regression models to estimate the associations between matching product attributes and SALA confusion. The models included a series of univariate (unadjusted) models, a model that adjusted for all product attributes, and a model that further adjusted for medication name similarity measures. Results: Medications with a matching product attribute had increased odds of SALA confusion in the univariate analyses (odds ratio [OR] = 4.2 to 55.5). When we simultaneously adjusted for all attributes, the associations of matching package unit, package unit size, formulation, strength, therapeutic class, and manufacturer with SALA confusion were attenuated but remained elevated (OR = 1.5 to 26.5), whereas the direction of association between matching route and SALA confusion reversed (OR = 0.8). These associations persisted on adjustment for medication name similarity measures. Conclusions and Relevance: This study is the first to evaluate the association between matching medication product attributes and SALA confusion with a control group. Having matching product attributes increased the odds of SALA confusion. SALA risk reduction strategies should consider product attributes.