CLIP: Harvard Pilgrim researchers develop model to reduce errors from sound-alike, look-alike medications

Researchers at the Harvard Pilgrim Health Care Institute developed and validated a data-driven prediction model to accurately identify sound-alike/look-alike (SALA) medication pairs to prevent potential errors. To conduct the study, the team from Harvard Pilgrim evaluated 82 medication name similarities and seven product attribute measures with 40,000 samples of medication pairs. They then created a prediction model comprised of 13 of the strongest predictors for potential medication errors, such as having the same first letter in the medication names or coming from the same manufacturer. Mistakes from SALA medications contribute to as many as 250,000 hospitalizations each year.