Critical decisions in oncology treatment today rely on understanding the molecular composition of the malignancy. In this era of rapidly changing technology, such as generative AI, discrete incorporation of molecular data including the results of DNA next-generation sequencing (NGS), RNA NGS, and immunohistochemistry testing remains essential for characterizing molecular cancer subtypes and selecting the right targeted therapies at the right doses. The electronic health record (EHR) is often considered to be a single location where clinicians review patient profiles, order molecular testing, and view results with associated treatment recommendations through clinical decision support (CDS) tools. However, EHRs were initially designed as billing tools rather than patient management tools, and may provide data without any insight, context, integration, or value to improve management.

Today, connectivity between molecular labs and EHR systems allows clinicians to not only order molecular testing directly through their EHR, but also receive test results discretely.

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