Healthcare Analytics / Business Intelligence
LTSS & Dual Eligible Analytics Command Center
A healthcare analytics environment designed to help leadership monitor LTSS and dual-eligible populations across enrollment, eligibility, utilization, case management, quality and cost.
The Business Problem
Leaders responsible for Long-Term Services and Supports (LTSS) and dual-eligible (D-SNP) populations often need to see enrollment, eligibility, utilization, case management, quality and cost together — yet that information typically lives in separate systems and reports.
This case study explores how a unified analytics environment can give leadership a single, trusted view of these populations.
The Vision
A command center where leadership can move from population-level trends to member-level drivers — enrollment, eligibility, member months, PMPM cost, utilization and quality — in a few clicks.
My Role
Challenges
The Solution
What was built, how it worked, how users interacted with it and how it addressed the business problem will be documented here as the build progresses.
Inside the Solution
Behind the Build
A polished interface is only the visible layer. This section shows the data, architecture, engineering and design decisions behind the finished solution.
Solution Architecture
- 1Source Systems
- 2Data Ingestion
- 3SQL / Python / ETL
- 4Databricks / Microsoft Fabric
- 5Data Model / Semantic Layer
- 6Power BI / Application
- 7Leadership / Operations / Clinical Users
Technology Stack
Business Intelligence
- Power BI — Executive and operational dashboards
- DAX — PMPM and member-month measures
- Power Query
Data Engineering
- Databricks
- Microsoft Fabric
- SQL
- Python
Development
- GitHub — Version control
Security, Privacy & Governance
Healthcare and AI solutions require more than functionality. They require deliberate attention to privacy, security, access, governance and responsible use.
Designed using HIPAA-aligned privacy and security principles.
Testing & Data Quality
- Eligibility validation
- Row-count validation
- Source-to-target validation
- Business-rule testing
Outcome
Demonstrated / Simulated Outcome
Outcome documentation is in progress. Results will be published here once validated against the demonstration dataset.
What I Would Build Next
- Predictive risk stratification for LTSS members
- Natural-language Q&A over the semantic model
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