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Description

About Us:

Astiva Health, Inc., located in Orange, CA is a premier healthcare provider specializing in Medicare and HMO services. With a focus on delivering comprehensive care tailored to the needs of our diverse community, we prioritize accessibility, affordability, and quality in all aspects of our services. Join us in our mission to transform healthcare delivery and make a meaningful difference in the lives of our members.

SUMMARY:

The Healthcare Data Analyst is responsible for analyzing healthcare data to support clinical, operational, and financial decision-making within Medicare Advantage programs. This role focuses on key areas including risk adjustment, quality measures (HEDIS and Star Ratings), pharmacy adherence, and claims analysis. 

The analyst collaborates with clinical, quality, pharmacy, and provider teams to identify trends, monitor program performance, and support CMS regulatory reporting. The role also includes developing automated data workflows and reporting solutions that deliver timely, actionable insights across the organization.

ESSENTIAL DUTIES AND RESPONSIBILITIES include the following:

Data Analysis & Reporting

• Analyze medical and pharmacy claims, membership, supplement, lab, risk adjustment, and encounter data to support Medicare Advantage quality, risk, and operational programs.
• Develop and maintain dashboards and reports for HEDIS, Star Ratings, medication adherence, RAF/HCC performance, and EDPS encounter data.
• Identify trends, care gaps, and performance opportunities to support quality improvement, pharmacy initiatives, and risk adjustment efforts.
• Provide analytics and reporting to MSOs/IPAs and internal teams, including quality, pharmacy, and risk adjustment.
• Support regulatory and CMS-related analyses, including encounter data monitoring, claims acceptance, and HCC performance.
• Deliver consolidated reporting and insights to leadership for strategic decision-making.
• Examine payments, cost of care, and utilization data to produce metrics for bid submission and JOMs or to address concerns from business partners.
• Support ad hoc reporting needs across the organization.

Data Quality & Validation

• Validate and reconcile claims, pharmacy, provider, membership, supplement, and lab data to ensure accuracy and completeness.
• Investigate and resolve data discrepancies, anomalies, and reporting issues across Medicare Advantage data sources.

Technical & Database Work

• Write and optimize SQL queries and stored procedures for data extraction, transformation, and analysis.
• Develop automated ETL workflows and data pipelines to support ongoing reporting needs.
• Work with large datasets in SQL Server and healthcare analytics platforms.
• Build dashboards and data visualizations using Power BI or SSRS.
• Utilize tools such as SQL Server, SSIS, Power BI, SSRS, Python, and Excel.

Collaboration

• Partner with clinical, pharmacy, quality, enrollment, credentialing, and finance teams to interpret results and support program initiatives.
• Assist with regulatory and compliance-related reporting requirements.
• Present findings and insights to both technical and non-technical stakeholders

Requirements

Required Qualifications

• Bachelor's degree in Data Analytics, Health Informatics, Statistics, Computer Science, or related field.
• 2-5+ years of healthcare data analytics experience.
• Knowledge of Medicare Advantage programs, HEDIS, and/or CMS Star Ratings.
• Advanced SQL skills for querying and analyzing large datasets.
• Experience with BI tools such as Power BI, SSRS, or similar tools.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience working in Medicare Advantage organizations, MSOs, or managed care settings.
• Knowledge of HCC risk adjustment, RAF methodologies, capitation payment model, DOFR, claim processing, bid design, and CMS regulatory requirements.
• Experience analyzing pharmacy adherence metrics (e.g., PDC).
• Familiarity with EDPS encounter data, claims submissions, and acceptance processes.
• Experience with ETL tools (e.g., SSIS) or programming languages such as Python or .NET.