Five interactive projects demonstrating how I think about go-to-market analytics, revenue cycle intelligence, and AI-powered insights for the specialty EHR space.
Built by Kristen Martino · All projects use synthetic or publicly available data (CMS NPPES, Medicare PUF, Census) · No proprietary data
These projects were built to demonstrate how I approach GTM business intelligence in the specialty healthcare EHR space. Each one addresses a specific analytical challenge that a GTM BI team faces: market sizing, sales funnel diagnostics, revenue cycle benchmarking, procedure trend monitoring, and AI-augmented analytics.
All data is synthetic or derived from publicly available sources (CMS NPPES provider registry, Medicare Physician PUF, Census Bureau, MGMA/HFMA published benchmarks). No proprietary or patient data was used.
Tech stack: React, Next.js, DuckDB-modeled data pipelines, Claude API (Anthropic) for natural language analytics. Each project is designed to be extensible with real data sources.