P.R. Hogan
Prescient Healthcare,
United States
Keywords: healthcare Analytics
Summary:
Rising healthcare costs and escalating workforce health risks represent a persistent economic, operational, and strategic challenge for large employers and public-sector organizations. Employer-sponsored and public health programs continue to face unsustainable cost growth driven by late intervention, fragmented data ecosystems, and limited executive visibility into emerging health risk trajectories. While population health analytics tools are widely available, most remain retrospective, siloed, and insufficiently actionable to support timely executive decision-making. As a result, healthcare leaders often lack the decision intelligence required to intervene upstream, allocate resources efficiently, and mitigate avoidable utilization before costs are realized. Prescient Healthcare has developed an AI-enabled Chief Medical Officer (CMO) Decision Intelligence Platform designed to address these gaps by operationalizing population-level health signals into real-time, economically grounded executive actions. The platform integrates multi-source administrative, clinical, and utilization data to detect emerging high-risk trajectories prior to downstream cost realization. Unlike traditional analytics dashboards that present descriptive metrics or static risk scores, the Prescient platform translates probabilistic risk signals into prioritized decision pathways by quantifying projected cost exposure, intervention timing, and expected return on intervention. This enables healthcare, finance, and workforce leaders to intervene earlier, align clinical actions with economic objectives, and measurably reduce total cost of care while improving workforce health outcomes. From a technical perspective, the platform combines supervised and unsupervised machine-learning models, longitudinal risk stratification, and advanced pattern recognition techniques to identify non-obvious drivers of avoidable utilization and cost escalation. Explainable AI methodologies are embedded throughout the system to ensure transparency, interpretability, and auditability—critical requirements for deployment in HIPAA-governed and public-sector environments. The platform is architected to integrate with existing data infrastructures and care delivery models, enabling rapid deployment within self-insured employer plans and public health programs without requiring disruptive system replacement or workflow redesign. This applied innovation directly aligns with SBIR/STTR priorities in digital health, applied artificial intelligence, workforce resilience, and cost-effective healthcare delivery. The platform addresses federal interests in reducing healthcare expenditure, improving population health management, and enhancing workforce readiness through earlier identification of health risks and more efficient allocation of care resources. Potential applications span multiple federal agencies and programs, including Department of Health and Human Services population health initiatives, Department of Defense beneficiary health management, Veterans Health Administration analytics programs, and state-level public employee health plans. The proposed work demonstrates a clear pathway from applied research to commercialization. Prescient Healthcare’s platform is designed as scalable decision-support infrastructure that can be deployed across employer, state, and federal environments, enabling measurable economic impact while supporting improved health outcomes. By shifting healthcare decision-making from retrospective analysis to proactive, intelligence-driven intervention, this innovation offers a sustainable approach to addressing one of the most pressing cost and workforce challenges facing the U.S. healthcare system.