Impresiv Health · 10 hours ago

EPIC Business Intelligence Reporting and Analytics Developer/Analyst

United States

Full-time

Remote

Mid Level

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Health CareManagement Consulting

Hiring Manager

JASMINE AVILES

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Responsibilities

Assess and interpret assigned PY8 QIP performance metric specifications with the SMEs.

Recommend to the SMEs the specific assigned QIP performance metrics that are achievable during PY8.

Recommend pseudocode documentation to identify population inclusion/exclusion logic and validate that logic with SMEs for PY8.

Prepare and implement the County approved pseudocode documentation and validate the assigned PY8 QIP performance metrics.

Peer test and unit test PY8 QIP performance metrics developed by the County.

Obtain the SME's approval on PY8 QIP performance metrics.

Provide data and other required Deliverables to support DHCS's PY8 QIP audit request.

Collate source documents and prepare the documentation for each solution and save in the County's Software Development Lifecycle repository for future reference by the County.

Prepare and provide County clinical and administrative leadership as well as health care providers with year-to-date metric performance reports, dashboards, and other analytics solutions to improve patient care, maximize metric performance, and achieve the highest possible, lawful QIP reimbursement from the State of California in PY8.

Qualification

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SQLQIP metrics experienceData structure designPay-for-performance programsSupplemental Program Development certificationPayor claims dataSoftware Development Life CycleData cleansing

Required

Excellent SQL skills and familiarity with all clinical and financial coding tables required

Metric experience with pay-for-performance programs like QIP or HEDIS Development of 'playbooks' for standardized coding required

Supplemental Program Development experience certification

Experience with payor claims and eligibility data elements and structures

Infrastructural skills in designing, transforming and using data structures including partitioning, data cleansing, to enable metric-related efficient queries. Balance between data structure and query load. Ability to interpret specs independently, evaluate pseudo code, and question decision points as appropriate