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 impacton these numbers, enhancing patient safety and improving drug efficacy. But while drug decision support isnow commonplace in Electronic Health Records (EHRs), many issues remain, and clinicians are generallyunsatisfied 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 overhalf 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 affectedby PGx interactions; and that nearly 98% of individuals have at least one actionable variant by currentguidelines. PGx findings are most commonly integrated into the EHR as non-actionable PDF reports. StructuredEHR-specific solutions are emerging, and several groups are experimenting with HL7 FHIR and CDS Hooksstandards. A common theme across these efforts is that PGx is implemented apart from other types ofmedication decision support, leading to disjointedness of alerts. For many years, groups have suggested theneed to integrate PGx with other types of identified medication interactions. Evidence suggests that such aholistic 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 obscuringthe 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 medicationalerting (such as drug-drug, drug-allergy, and drug-condition), thereby enhancing patient safety throughminimization 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, simulatedby a HAPI FHIR server; FHIR-formatted genomic data, in this case from Elimu's genomic data server; and drugknowledge, in this case from First DataBank and PharmGKB. The service translates identified interactions intonormalized data elements which are exposed as structured FHIR DetectedIssues, one DetectedIssue perinteraction. The PillHarmonics service will be demonstrated via a CDS Hooks application that generatesintegrated alerts in response to the addition of tacrolimus or clopidogrel to a patient's existing medicationregimen. AIM 2 evaluation will entail a "perceived usefulness' assessment of the PillHarmonics algorithm usingan established evaluation instrument.
Public Health Relevance Statement: Project Narrative While many types of drug decision support are now commonplace in Electronic Health Records (EHRs), many issues remain. Attempts at integration of pharmacogenomics (PGx) into the EHR winds up surfacing these shortcomings, making it hard to integrate PGx in a way that maximizes clinical utility. 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.
