The **MEMBERS ONLY**SIGN UP NOW***. Information Management & Analytics (CIMA) unit offers innovative solutions that provide actionable insights to internal and external business partners and customers that help reduce health costs, improve outcomes, provide financial security and measure/forecast business performance. The Data Science team of provider specialty care collaboration drives the design and evaluation of new and/or enhanced innovative pay-for-performance (P4P) initiatives to be implemented and tested as part of **MEMBERS ONLY**SIGN UP NOW***.’s Collaborative Care P4P strategy. This individual will be responsible for conducting advanced analytics, research activities, and program evaluations in efforts to design and develop the specialty value-based care programs. This role will work independently and collaboratively with key technical and non-technical matrix partners within organization.
So, you’re excited and motivated to take over this challenging role by becoming the newest member of this team? Great choice! Let’s check some boxes to see if you fit the bill:
• Perform exploratory and advanced analytics to answer “ what happened?”
• Conduct root cause statistical analyses to answer “ why did this happen?”
• Mine data to answer “ where are the opportunities?”
• Deploy innovation value-based solutions to answer “ how can we improve affordability and quality of care?”
• Rabid desire to learn new techniques and enjoy problem solving?
This person will be conducting advanced and exploratory analytics, generating actionable insights and resources to strategically design and/or enhance specialist’s pay for performance programs.
• Collaborate and work closely with stakeholders to design and evaluate Value Based Payment programs. Example areas include hospital and physician Accountable Care Organization (ACO) programs, Episodes of Care/Bundle programs, Oncology Medical Home, etc.
• Conduct statistically and clinically robust program design and evaluations using advanced analytic techniques including but not limited to risk adjustment, episode analytics (ETG, Prometheus etc.), statistical modeling, power analysis, matched case control studies etc.
• Derive actionable insights from healthcare data (claims, clinical, pharmacy, externally sourced) to engage and enable our provider/clinical partners. Support IM/IT to deploy the actionable insight into accessible solutions for our provider/clinical partners
• Present analytic findings and recommendations to non-technical business partners and leadership to drive data driven strategies
• Explore innovative solutions to business questions/problems
• Supervise, coach, and develop colleagues
This position requires healthcare and insurance content knowledge, analytics/data science expertise and value based program expertise to support **MEMBERS ONLY**SIGN UP NOW***. on Pay-for-performance strategy.
• Advanced degree or equivalent experience in Statistics, Biostatistics, Epidemiology, Health Outcomes Research, Actuarial Science, or Data Science
• At least 5 years’ experience in related healthcare analytics or value-based care research
• Working clinical knowledge on specialty conditions and deep understanding of health care and delivery system processes
• Strong technical skills to extract, transpose, and analyze Big Data using SAS/Teradata/Hadoop/Oracle and output through advanced visualization tools including, but not limited to, VBA/Tableau/R/Python/GIS
• Subject matter expert in healthcare cost and quality metrics, including but not limited to various episode models (ETG, Prometheus, etc.), quality measures (HEDIS, PQRS etc.), and provider value-based programs
• Ability to successfully navigate and contribute in a highly-matrixed environment
• Emerging track record of presentations / publications and thought leadership
• Strong Healthcare data knowledge (medical claims data, clinical data, pharmacy data and eligibility data)
• Subject matter expert on Value Based Payment programs (ACO, bundles, episodes, etc.)
• Strong knowledge and experience with analytic tools and applications like episode analytics and risk adjustment
• Statistical training in school or through work (ability to formulate and execute appropriate confidence intervals, power analysis, bootstrapping, regression modeling, etc.)
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