HL7 v2 in 2026: Why This 50-Year-Old Protocol Still Drives Healthcare Integration
Why HL7 v2 — a 50-year-old pipe-delimited protocol — still drives most US hospital ADT integrations in 2026, and what a clean Go parser looks like in ~300 lines.
Archive
103 posts · Page 2 of 9. ← Blog
Studying for the AIGP? Here's a Reference Implementation in Go
Studying for the IAPP AI Governance Professional credential? Here's an open-source Go codebase that demonstrates ~70% of the body of knowledge in working code.
"Enough to Reconstruct, Never Enough to Leak": The HIPAA Audit Log Design Problem
Enough to reconstruct, never enough to leak. The audit event schema problem under §164.312(b), and how to solve it without conflating the audit sink with the PHI sink.
The Fallback Is the Contract: Reliability Patterns for Clinical AI
Every LLM-backed agent in this platform has a deterministic rule-based fallback. The case always finalises. The fallback isn't a workaround — it's the contract.
Multi-Agent Systems in 5 Interfaces: A MARA Implementation Field Report
Five interfaces hold the whole platform together. The 30-line orchestrator closure that makes the rest of the architecture testable, auditable, and safe to evolve.
PostgreSQL Row-Level Security Is HIPAA Defense in Depth
PostgreSQL row-level security as HIPAA defence in depth. Why fail-open application filtering isn't enough, and how 'append-only at DB GRANTs' carries more of the §164.312(b) burden than people realise.
The 21st Century Cures Act, Expressed in Go
The 21st Century Cures Act §3060 CDS carve-out criterion 4 expressed as a code-level queue, lossless on reject, with audit-recorded reviewer rationale. Build it once, satisfy GDPR Article 22 for free.
Moving Diagnostic Accuracy 42.9% → 85.7% by Changing Two Files
How a single sprint of specialty-rule work — guided by a benchmark that wasn't afraid to print embarrassing numbers — turned a 'demo respiratory differential' into a five-condition rule-based diagnostic engine.
Building a HIPAA-Aware Medical AI Platform in Go: An Architecture & Compliance Deep Dive
What HIPAA looks like when you express it as Go interfaces — governance policies, append-only audit at DB GRANTs, PHI redaction at the logger seam, and HITL as the §3060 CDS carve-out criterion 4.
The MERGE pattern that cost ten times more than INSERT-then-UPDATE — a ₹100 Cr lesson
What looked like an idiomatic BigQuery MERGE was scanning the full target table on every batch. The fix was syntactic, not architectural — and it was the single biggest contributor to a 57% data-warehouse cost reduction across the Tata Group engagement.
The 57% number — how we cut the Tata Group BigQuery bill in half
₹100 Cr / ~$12M in proven savings across a year-plus engagement. The four levers that did the heavy lifting, the lever I expected to win that didn't, and the post-engagement playbook that became a Searce managed service.
Optimus — a Gemini-powered BigQuery anti-pattern detector that paid for itself in a week
We built a small Go + Python service that parses a project's INFORMATION_SCHEMA, asks Gemini to classify each top-spending query against a catalog of anti-patterns, and recommends a rewrite. It is not a magic box; it is a pipeline that cuts the human review time per query from 20 minutes to 90 seconds.