Fast Healthcare Interoperability Resources (FHIR)–Based Quality Information Exchange for Clinical Next-Generation Sequencing Genomic Testing: Implementation Study (Preprint)

Abstract

BACKGROUND Next Generation Sequencing (NGS) technology has been rapidly adopted in clinical practice, and the scope of clinical NGS applications has been extended to early diagnosis, disease classification, and treatment planning. As the number of requests for NGS genomic testing increases, substantial efforts have been made to deliver the testing results clearly and unambiguously. For the legitimacy of clinical NGS genomic testing, quality information from the process of producing genomic data should be included within the results. However, most reports provide insufficient quality information to confirm the reliability of genomic testing due to the complexity of the NGS process. OBJECTIVE The goal of this study was to develop an NGS Quality Reporting (NGS-QR) app, a Fast Healthcare Interoperability Resources (FHIR) based web application, to report and manage the quality information of clinical NGS genomic tests. METHODS We defined data elements for the exchange of quality information from clinical NGS genomic tests, and profiled a FHIR genomic resource to exchange in a standardized method. Then, we developed a FHIR-based web application and FHIR server to exchange quality information and implemented the R Shiny server to provide statistical analysis in the application. RESULTS Approximately 1,000 experimental data were collected from the targeted sequencing platform CancerSCAN designed by the Samsung Medical Center. Herein, we demonstrated the NGS-QR app using real-world data. The user can share the quality information of NGS genomic testing and verify the quality status of individual samples in the overall distribution. CONCLUSIONS This study successfully demonstrated how quality information of clinical NGS genomic testing can be exchanged in a standardized method. As the demand for NGS genomic testing increases and genomic data accumulates, quality information can be used as reference materials to improve the quality of testing. It could also motivate laboratories to perform diagnostic tests to provide high-quality genomic data.