Changes in non-small cell lung cancer (NSCLC) next-generation sequencing (NGS) rates after electronic health record (EHR) integration using large-scale, multi-institutional, real-world data

ASCO 2024 Abstract
Authors Marc Ryan Matrana, Patrick Mergler, Leo Posteraro, James Lin Chen

Background: NSCLC treatment guidelines recommend comprehensive NGS testing to detect genomic alterations and gene expression in key biomarkers that are relevant in diagnosis, therapy selection, prognosis, and clinical trials. While 70% of patients with NSCLC will have biomarker alterations related to therapeutic options, a large minority of patients still do not receive biomarker testing. Clinical workflow challenges outside the EHR ecosystem, like paper requisitions and faxed results, have been cited as barriers to adoption. To reduce sequencing barriers, Tempus deploys NGS through direct result EHR connection. To evaluate whether integrating comprehensive NGS ordering and resulting into the EHR would improve testing rates, we retrospectively analyzed NSCLC NGS orders from 29 clinical networks which represent over 1500 medical oncologists, before and after EHR integration.

Methods: Clinical networks that partnered with Tempus to perform an NGS EHR integration were identified. Only networks with at least 6 months of pre- and post-integration unique patient NGS orders were included. De-identified patient information from these sites were obtained from the Tempus laboratory information management system. NSCLC diagnosis was determined through ICD9/10 codes. NGS tests ordered were limited to xT/xR (solid tumor DNA and RNA), xE (solid tumor whole exome), or xF (circulating tumor DNA). Aggregate unique patients with orders were summated on a per site basis. Descriptive statistics were used to characterize the findings.

Results: From May 2019 to July 2023, 29 clinical cancer networks (48% academic medical center, 45% regional health system) that underwent a Tempus NGS EHR integration were identified. Of the 29 networks considered, 3 were excluded due to insufficient data. Of the evaluable 26 networks, Epic EHR was used in the majority (24 of 26). In aggregate, a total of 1825 NSCLC patients were sequenced pre-integration as compared to 2796 patients sequenced post-integration, representing a 53% increase. Academic medical centers experienced a higher increase versus regional health systems (65% v 48%). When examined on a per network basis, the median and mean increase in NSCLC patients sequenced were 49% and 118%, respectively.

Conclusions: In this retrospective analysis, Tempus EHR integrations increased ordering of comprehensive NSCLC NGS by 53%. Despite study limitations such as the incomplete resolution into internal alternate sequencing workflows, this large-scale analysis provides further evidence that EHR-based workflow improvements reduce the barrier to appropriate sequencing.