Rui Zhang and Matt Loth Help Develop Phenotyping Algorithm

Rui Zhang, PhD, and Matt Loth, PhD, from the Innovative Methods & Data Science program worked with lead author Boguang Sun and a team of other University of Minnesota researchers to develop and validate a phenotyping algorithm for pharmacological statin-associated muscle symptoms (SAMS).

Statins are common cholesterol-lowering medications which are widely associated with muscle issues, or SAMS, as a side effect. However, incidents of SAMS which are caused by the statin directly (pharmacological SAMS) and those caused by the nocebo effect are difficult to distinguish.

The research team developed algorithms that are able to identify cases of pharmacological SAMS using data from Electronic Health Records (EHR) in the Fairview EHR system. Out of the algorithms, a combined rule-based (CRB) algorithm that uses structured data and clinical notes performed the best.

The researchers applied the CRB algorithm to a larger group of Fairview patients taking statins to identify cases of pharmacological SAMS and risk factors for the condition.

A preprint of the NIH-funded study is available on PubMed.