Sunday, May 11, 2025
5/11/2025
PillHarmonics: An Orchestrated Medication Clinical Decision Support Service - Project Summary Medication related adverse events account for over 2 million hospital stays and 3.5 million physician office visits per year. Medication decision support, when implemented correctly, can have a significant impact on these numbers, enhancing patient safety and improving drug efficacy. But while drug decision support is now commonplace in Electronic Health Records (EHRs), many issues remain, and clinicians are generally unsatisfied with the lack of patient specificity and inappropriate context of medication alerts. Add to this the fact that drug-gene alerts are becoming increasingly important. Studies show that over half of all primary care patients are exposed to pharmacogenomics (PGx) relevant drugs; that 7% of FDA- approved medications and 18% of the 4 billion prescriptions written in the United States per year are affected by PGx interactions; and that nearly 98% of individuals have at least one actionable variant by current guidelines. PGx findings are most commonly integrated into the EHR as non-actionable PDF reports. Structured EHR-specific solutions are emerging, and several groups are experimenting with HL7 FHIR and CDS Hooks standards. A common theme across these efforts is that PGx is implemented apart from other types of medication decision support, leading to disjointedness of alerts. For many years, groups have suggested the need to integrate PGx with other types of identified medication interactions. Evidence suggests that such a holistic approach can address patient safety issues (e.g., by juxtaposing conflicting drug recommendations) and alert fatigue (e.g., through greater alert precision). However, merging PGx into an environment that already has many usability challenges risks obscuring the benefits of such alerts. In response, this project aims to develop a medication decision support service, ‘PillHarmonics’, that seamlessly integrates drug-gene interaction checking with other types of medication alerting (such as drug-drug, drug-allergy, and drug-condition), thereby enhancing patient safety through minimization of adverse drug events and decreasing alert fatigue via more precise surfacing of relevant alerts. In the planned prototype, PillHarmonics will gather FHIR-formatted clinical data from an EHR, simulated by a HAPI FHIR server; FHIR-formatted genomic data, in this case from Elimu’s genomic data server; and drug knowledge, in this case from First DataBank and PharmGKB. The service translates identified interactions into normalized data elements which are exposed as structured FHIR DetectedIssues, one DetectedIssue per interaction. The PillHarmonics service will be demonstrated via a CDS Hooks application that generates integrated alerts in response to the addition of tacrolimus or clopidogrel to a patient's existing medication regimen. AIM 2 evaluation will entail a ‘perceived usefulness’ assessment of the PillHarmonics algorithm using an established evaluation instrument.
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