A computational approach to identify interfering medications on urine drug screening assays without data from confirmatory testing

Background Urine drug screening (UDS) assays can rapidly and sensitively detect drugs of abuse, but can also produce spurious results due to interfering substances. We previously developed an approach to identify interfering medications using electronic health record (EHR) data, but the approach was limited to UDS assays for which presumptive positives were confirmed using more specific methods. Here we adapted the approach to search for medications that cause false positives on UDS assays lacking confirmation data.