FormDR processes 6.6M clinical events per week. HIPAA compliance was assumed but never audited end-to-end. One data flow mapping exercise changed everything.
FormDR is a healthcare forms platform that processes clinical intake, questionnaires, consent documents, and patient communications. The platform handles 6.6M clinical events per week across 12 major practice deployments, supporting everything from routine check-in forms to mental health screening instruments.
PostHog was deployed as the analytics layer — chosen for its HIPAA-compliant cloud offering with a signed BAA in place. The configuration was standard: autocapture enabled on most surfaces, session recording active for UX analysis, GeoIP enrichment on by default. Everything the documentation said should work for a BAA-covered deployment.
The team had never audited what the analytics pipeline was actually ingesting. HIPAA compliance was assumed by contract, but no end-to-end data flow mapping had ever been done. The BAA covered PostHog as a processor. It did not cover what the client’s own SDK configuration was sending into the pipeline.
A systematic audit of PostHog event properties, autocapture output, SDK configuration, session recording metadata, and tracked URL patterns identified 8 distinct categories of PHI exposure in the live analytics pipeline. Each finding was classified against 45 CFR 164.514(b)(2) Safe Harbor de-identification standards.
Rather than disable analytics on clinical surfaces entirely — which would have removed the team’s ability to measure product engagement — we designed a layered defence that scrubs PHI at four distinct points in the ingestion pipeline.
Your compliance team has a complete audit trail: 8 PHI exposure categories documented with the exact source location, data type, and regulatory classification for each. Every remediation action is traceable to the specific finding that triggered it. The weekly scan job provides ongoing verification — not a one-time snapshot but continuous monitoring.
Your product team kept full analytics visibility. The 4-layer scrubber didn’t disable analytics — it filtered out PHI while preserving all non-PHI event data and session recordings. Engagement metrics, feature adoption, funnel analysis, and cohort retention all remained intact. No data loss. No blind spots.
The scan tooling is open-source and reusable. Any PostHog deployment with HIPAA, GDPR, or SOC 2 requirements can adopt the same weekly scan approach. The patterns and allowlist methodology are documented and transferable — not tied to the specific SDK configuration that triggered the audit.
10 years building analytics and growth systems for B2B SaaS at $1M–$50M ARR. BSc Behavioural Psychology, MSc Data Science. HIPAA analytics compliance is not about the BAA — it’s about what your SDK configuration actually sends before the BAA-covered processor touches it. The gap between assumed compliance and actual data flow is usually where the exposure lives.
A structured end-to-end data flow audit of your analytics pipeline — identifying every PHI exposure point before a compliance review or breach notification finds them for you.
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