Director, Medical Economics

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SCAN Group is a not‑for‑profit organization dedicated to tackling the most pressing issues facing older adults in the United States. SCAN Group is the sole corporate member of SCAN Health Plan, one of the nation’s leading not‑for‑profit Medicare Advantage plans, serving more than 277,000 members in California, Arizona, Nevada, Texas and New Mexico. SCAN has been a mission‑driven organization dedicated to keeping seniors healthy and independent for more than 45 years and is known throughout the healthcare industry and nationally as a leading expert in senior healthcare.

SCAN employees are a group of talented, passionate professionals who are committed to supporting older adults on their aging journey, while also innovating healthcare for seniors everywhere. Employees are provided in‑depth training and access to state‑of‑the‑art tools necessary to do their jobs, as well as development and growth opportunities. SCAN takes great pride in recognizing our team members as experts in their fields and rewarding them for their efforts.

If you are interested in becoming part of an organization that is innovating senior healthcare, visit (Use the "Apply for this Job" box below). , or follow us on Linked In, Facebook, and Twitter.

• Identify trends across all drivers of cost of care on a granular level (unit cost vs. utilization, site‑of‑care, provider/facility variation, pharmacy, post‑acute, out‑of‑network/leakage, etc.) and deliver standardized executive updates on a regular cadence highlighting root causes, mitigation actions, forecast implications, and emerging headwinds.
• Develop and oversee a portfolio of scored tangible activities (STAs) to quantify how medical management activities (UM/CM/Med Policy) affect total cost of care, translate initiative lift into measurable PMPM impact, and incorporate in‑flight initiatives into forecasts with clear assumptions and variance‑to‑plan reporting; provide ad‑hoc analytics support for SCAN’s Care Delivery Assets and joint‑venture partnerships.
• Own provider performance and variation analytics (medical group/IPA/facility/specialist), including referral patterns, site‑of‑care, unit cost vs utilization decomposition, episode/case‑mix aware comparisons, and intervention targeting.
• Lead provider contract & performance analytics to support negotiation strategy and performance terms (capitation, shared savings/loss, corridors, quality withholds, reconciliation approaches).
• Evaluate provider risk arrangement transitions (capitation → shared risk/at‑risk models, new VBC structures), including scenario modeling, sensitivity analysis, expected ROI, downside exposure, and operational readiness considerations.
• Drive network adequacy and optimization analytics, including geo‑mapping, access/capacity determinations, leakage/capture, opportunities to strengthen partnerships, and recommendations for network design changes.
• Determine impact measurement strategy for medical economics & network analytics: KPI definitions, evaluation standards, governance, and an aligned analytics roadmap.
• Partner with Clinical Ops (UM/CM/Medical Policy) to develop operational analytics: prior auth/denial drivers, turn‑around time, escalations, approvals by policy, avoidable admissions/readmissions, SNF/post‑acute patterns, and program effectiveness; establish feedback loops to policies and workflows; partner closely with SCAN’s managers, FP&A, Pharmacy, and other stakeholders, as well as the broader Data & Analytics team.
• Build pharmacy economics insight across Part D (trend, mix, formulary impact, specialty and high‑cost drivers, adherence/persistence where relevant) and Part B (J‑codes, buy‑and‑bill dynamics, site‑of‑care shifts, infusion/imaging policies), aligning with clinical programs and contracting strategies.
• Oversee risk stratification and predictive analytics to identify emerging high‑cost members and utilization risk (e.g., inpatient risk, ED risk, post‑acute risk, specialty drug risk), support targeted UM/CM interventions, prioritize provider/program opportunities, and monitor model performance/drift with clear governance and explainability.
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