Knezevic Claire E, Stevenson James M, Merran Jonathan, Snyder Isabel, Restorick Grant, Waters Christopher, Marzinke Mark A
Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Division of Clinical Pharmacology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
J Appl Lab Med. 2025 Mar 3;10(2):259-273. doi: 10.1093/jalm/jfae128.
Pharmacogenomics has demonstrated benefits for clinical care, including a reduction in adverse events and cost savings. However, barriers in expanded implementation of pharmacogenomics testing include prolonged turnaround times and integration of results into the electronic health record with clinical decision support. A clinical workflow was developed and implemented to facilitate in-house result generation and incorporation into the electronic health record at a large academic medical center.
An 11-gene actionable pharmacogenomics panel was developed and validated using a QuantStudio 12K Flex platform. Allelic results were exported to a custom driver and rules engine, and result messages, which included a diplotype and predicted metabolic phenotype, were sent to the electronic health record; an electronic consultation (eConsult) service was integrated into the workflow. Postimplementation monitoring was performed to evaluate the frequency of actionable results and turnaround times.
The actionable pharmacogenomics panel covered 39 alleles across 11 genes. Metabolic phenotypes were resulted alongside gene diplotypes, and clinician-facing phenotype summaries (Genomic Indicators) were presented in the electronic health record. Postimplementation, 8 clinical areas have utilized pharmacogenomics testing, with 56% of orders occurring in the outpatient setting; 22.1% of requests included at least one actionable pharmacogene, and 67% of orders were associated with a pre- or postresult electronic consultation. Mean turnaround time from sample collection to result was 4.6 days.
A pharmacogenomics pipeline was successfully operationalized at a quaternary academic medical center, with direct integration of results into the electronic health record, clinical decision support, and eConsult services.
药物基因组学已证明对临床护理有益，包括减少不良事件和节省成本。然而，药物基因组学检测扩大实施的障碍包括周转时间延长以及将结果整合到具有临床决策支持功能的电子健康记录中。在一家大型学术医疗中心开发并实施了一种临床工作流程，以促进内部结果生成并将其纳入电子健康记录。
使用QuantStudio 12K Flex平台开发并验证了一个包含11个基因的可操作药物基因组学检测板。等位基因结果被导出到一个定制驱动程序和规则引擎，包含双倍型和预测代谢表型的结果信息被发送到电子健康记录；电子会诊（eConsult）服务被整合到工作流程中。实施后进行监测，以评估可操作结果的频率和周转时间。
可操作药物基因组学检测板涵盖11个基因的39个等位基因。代谢表型与基因双倍型一同得出，面向临床医生的表型总结（基因组指标）在电子健康记录中呈现。实施后，8个临床领域使用了药物基因组学检测，56%的检测申请发生在门诊环境；22.1%的申请至少包含一个可操作的药物基因，67%的检测申请与检测前或检测后的电子会诊相关。从样本采集到结果的平均周转时间为4.6天。
在一家四级学术医疗中心成功实施了药物基因组学流程，结果直接整合到电子健康记录、临床决策支持和电子会诊服务中。
