We’re happy to announce that a poster that we co-authored with our customer Sanford Health was chosen as a Featured Poster at the Individualizing Medicine 2015 conference hosted by the Mayo Clinic earlier this week. The poster, “Rapid implementation of a system-wide, high-throughput, EHR-integrated pharmacogenetics clinical service through cloud-based software automation,” describes how Syapse Precision Medicine Platform? enabled Sanford to integrate pharmacogenetics test results into clinical workflow. The Syapse platform automated what was previously a manual, labor-intensive, and error-prone process, streamlined the delivery of clinically actionable results to the electronic medical record, and enabled real-time alerts in the electronic medical record at the time of drug ordering.
You can read the abstract below and check out the full poster here.
Adoption of precision medicine has the potential to improve quality of care while reducing toxicity, unnecessary treatments, and cost. In particular, availability of pharmacogenetics (PGx) data before a drug is ordered can improve patient safety. Sanford Health is one of the largest health systems in the nation with 43 hospitals and nearly 250 clinics. In 2014, we initiated a program to integrate genomic medicine into adult primary care. A priority was implementation of a system-wide PGx clinical service with 3 components: 1) Fast-turnaround in-house analysis of drug metabolism genes, 2) delivery of clinically actionable results to the electronic health record (EHR) system, and 3) integration of PGx results into clinical workflow via real-time alerts at the time of drug ordering. To ensure accurate decision support based on clinically valid gene-drug relationships, the in-house panel only contains genes with clear clinical dosing guidelines published by the Clinical Pharmacogenetics Implementation Consortium (CPIC), including CYP2C19, CYP2D6, CYP2C9, CYP3A5, VKORC1, TPMT, and DPYD. Syapse Precision Medicine Platform (PMP) software was used to automate receipt of test orders from the EHR, convert nucleotide-based genotyping results to corresponding star (*) alleles, and convert star alleles to enzyme metabolizer status. Results were then automatically delivered back to the EHR. To determine the efficacy of Syapse PMP for clinical PGx services, we compared manual entry, data review, and result reporting of 60 samples to automated processing by Syapse PMP. The manual process had a 5% error rate and took over 20 person-hours. One sample had an incorrectly spelled last name, one had the incorrect gender, and another was reported as wild-type for CYP2C19 instead of *1/*2 and thus would have been misreported as an extensive metabolizer instead of intermediate. Using Syapse PMP, no manual sample entry was required, eliminating the need for paper requisition forms. Data review and reporting were reduced to 2 hours, with no processing errors. Automation with Syapse PMP enabled Sanford Health to implement a clinical PGx service in less than 5 months and trigger best-practice alerts with patient-specific decision support content to fire upon ordering of a corresponding drug in the EHR.