Reducing Drug Name Confusion with Better Search Software

DESCRIPTION (provided by applicant): Confusions between drug names that look and sound alike (e.g., Indocid(r) and Endocet(r)) continue to occur frequently, and each error threatens patient safety. Drug companies and regulators try to avoid confusion by screening new names prior to approval, but the effectiveness of screening is limited by over-reliance on subjective assessments of confusability, small sample sizes, lack of expertise in psycholinguistics, and weak empirical validation of testing methods. The FDA recently adopted a system that can search separately for similar names based on spelling or phonetic similarity, but optimal results will be achieved by combining the results of multiple search engines, where each distinct search engine implements a different similarity measure. Our long term objective is to design, build, test and continuously improve tools that help decision makers minimize the incidence of drug name confusion errors. Our short-term goal is to develop and validate several new techniques for merging the results of distinct search engines. Given a name as input, the search engine will return a merged list of existing names ranked in descending order of confusability. Confusability ratings will be based on validated, objective criteria derived from studies of clinicians' and lay persons' memory errors, perceptual errors, and similarity judgments. To further these goals, we plan to test the following hypothesis: The performance of a drug name metasearch engine that merges the results of multiple, distinct first-order searches will be superior to a search engine using a single measure of similarity. To test these hypotheses, we propose studies with the following specific aims: 1. To design and implement several different algorithms for merging the ranked results of separate drug name search engines. 2. To evaluate the alternative merging techniques in relation to previously reported errors, results of behavioral tests, and expert similarity judgments. 3. To incorporate the merging algorithms into a web-accessible, user-friendly search engine that can be used to support decision making during the drug name approval process.