556 Background: Comprehensive biomarker testing is foundational to delivering guideline-concordant precision oncology. However, real-world data consistently show underutilization in community settings, contributing to treatment disparities and suboptimal outcomes. We evaluated the impact of a collaborative, clinical decision support (CDS) -driven initiative to standardize biomarker testing in a large community oncology practice, supported by a payer and a precision medicine technology partner. Methods: A two-year program (2022–2024) integrated a CDS platform into the clinical workflows of a prominent community oncology network, supported by a large managed Medicaid and Marketplace insurer. The platform provided real-time guidance based on NCCN Guidelines, FDA labels, and payer coverage policy for 20 solid tumor types. Metrics evaluated included adherence to guideline-recommended testing, ordering efficiency, in-network lab utilization, prior authorization (PA) burden, and cost of care. A follow-up user survey captured clinical experience. Results: Across 20 tumor types, The program served 393 elligible plan members. 94% of patients received guideline-recommended biomarker testing. Platform-configured test sets were used in 86% of orders; value-based in-network options were selected 43% of the time. These patterns led to an 8% increase in in-network lab utilization and a 38% reduction in average per-claim costs (850 savings). PA burden was reduced via pre-authorization alignment with payer policy. A clinician survey (27% response rate) showed that 96% found the platform intuitive, and average test ordering time dropped from ~20 to 3 minutes. Conclusions: This payer-provider-CDS collaboration successfully nudged concordance with standard-of-care biomarker testing, reduced health plan spending, and improved workflow efficiency. The model demonstrates scalable potential to address disparities in molecular testing and improve access to precision oncology in the community setting—advancing quality and equity in cancer care through collaborative use of clinical decision support.
Brisbin et al. (Wed,) studied this question.
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