Development of a point-of-care clinical decision support system to optimize total cost of care, while preserving quality outcomes: Integration of economic, clinical, pathological, genomic data, and national guidelines.

Abstract

e23301 Background: Rising cancer care costs challenge patients and policymakers, with approximately 80% of expenditures driven by physician decisions at the point of care. National guidelines (ASCO/NCCN) emphasize clinical efficacy but rarely incorporate economic impact. Prior work demonstrated cost variation exceeding $50,000 among comparable cohorts of breast, colorectal, and lung cancer pts (Pecora; J Prec Med 2020). We developed an artificial intelligence–enabled clinical decision support (CDS) system that integrates clinical, pathological, and genomic data with evidence-based national guidelines and cost estimates. Methods: We conducted a retrospective cost analysis of stage I–III breast cancer using the CDS platform. The tool synthesizes multidimensional patient data and presents NCCN/ASCO-supported treatment pathways with projected, practice-specific costs. The primary endpoint was estimated cost savings, defined as the difference between 1-year total cost of care recommended by the oncologist and by the CDS. Costs reflected medical oncology only (excluding radiation/surgery) and were standardized using Medicare fee schedules, adjusted for temporal bias (2020–2022) and for insurance fee bias. Consecutive stage I–III breast cancer pts treated at a large community practice and an academic cancer center (2020–2022) were identified, with clinical data extracted from the EMR. Only complete cases with 1-year follow-up were analyzed. IRB approval was obtained with waiver of informed consent. Results: Patients were stratified into risk-adjusted cohorts by stage and prognostic/predictive factors, including genomic data. Of 2,434 records reviewed, 1,188 pts had complete data (579 hospital-based). The CDS identified mean potential cost savings of 21.8% ($7,160 per pt). In a pilot intervention displaying guideline-concordant options alongside comparative costs, physician pathway selection shifted, yielding a 15–20% reduction in calculated 1-year total costs. Conclusions: Integrating economic insights into point-of-care oncology decision-making facilitates value-based care without compromising guideline adherence or quality. This approach enables cost-sharing models between payers and providers while maintaining evidence-based treatment. The CDS is currently piloted in a large multicenter oncology practice, with broader implementation underway in partnership with a major healthcare payer. Breast cancer: 1 year estimated total cost of care. Patients Initial Treatment Cost Savings Opportunity % Reduction Stage I 707 $13,795,728.02 $3,636,927.32 26.36% Stage II 391 $18,977,328.88 $3,371,674.01 17.77% Stage III 90 $7,066,640.88 $1,497,921.41 21.20% Total 1188 $39,851,243.58 $8,506,522.74 21.35%