AI Article Synopsis

  • Next-generation sequencing (NGS) is crucial for precision oncology, but there are significant challenges in integrating genomic data into electronic health records and clinical workflows.
  • This review analyzes the problems with inconsistent data standards and the interoperability of genomic data systems, proposing potential solutions.
  • Current genomic databases and standards like HL7 FHIR and mCODE are evolving but not yet fully implemented; improved management of genomic data through universal standards and better tools is essential for effective patient care.

Article Abstract

Purpose: Next-generation sequencing (NGS) of tumor and germline DNA is foundational for precision oncology, with rapidly expanding diagnostic, prognostic, and therapeutic implications. Although few question the importance of NGS in modern oncology care, the process of gathering primary molecular data, integrating it into electronic health records, and optimally using it as part of a clinical workflow remains far from seamless. Numerous challenges persist around data standards and interoperability, and clinicians frequently face difficulties in managing the growing amount of genomic knowledge required to care for patients and keep up to date.

Methods: This review provides a descriptive analysis of genomic data workflows for NGS data in clinical oncology and issues that arise from the inconsistent use of standards for sharing data across systems. Potential solutions are described.

Results: NGS technology, especially for somatic genomics, is well established and widely used in routine patient care, quality measurement, and research. Available genomic knowledge bases play an evolving role in patient management but lack harmonization with one another. Questions about their provenance and timeliness of updating remain. Potentially useful standards for sharing genomic data, such as HL7 FHIR and mCODE, remain primarily in the research and/or development stage. Nonetheless, their impact will likely be seen as uptake increases across care settings and laboratories. The specific use case of ASCO CancerLinQ, as a clinicogenomic database, is discussed.

Conclusion: Because the electronic health records of today seem ill suited for managing genomic data, other solutions are required, including universal data standards and applications that use application programming interfaces, along with a commitment on the part of sequencing laboratories to consistently provide structured genomic data for clinical use.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7446333PMC
http://dx.doi.org/10.1200/PO.19.00232DOI Listing

Publication Analysis

Top Keywords

genomic data
16
data
10
next-generation sequencing
8
clinical oncology
8
electronic health
8
health records
8
data standards
8
genomic knowledge
8
data clinical
8
standards sharing
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!