Technical deep-dives, clinical perspective, and practical guidance from the people building the future of healthcare AI.
Most healthcare AI initiatives fail not because the models are wrong, but because production infrastructure is an afterthought. We examine what it takes to move clinical AI from promising pilot to reliable, compliant production deployment — and why the gap is almost entirely an infrastructure problem.
Atul Grover
March 10, 2026
HL7 v2 has powered healthcare messaging for 40 years. FHIR R4 is the future. Understanding the architectural differences — from segment-based EDI to RESTful resources — is essential for any team building modern healthcare integrations.
Chan Harjivan
February 28, 2026
The Model Context Protocol (MCP) defines a standard contract for how AI agents discover and call tools — including FHIR queries, lab result interpretation, and clinical documentation. This deep-dive walks through building a FHIR-native clinical agent on the HealthCloud MCP server.
Bojan Miše
February 15, 2026
Many developers treat HIPAA as a documentation exercise. It is not — it is an architecture discipline. This post walks through 8 concrete technical controls required for PHI-touching AI systems, including de-identification pipelines, audit log requirements, and BAA scope.
Dan Hanfling
February 5, 2026
Collecting device data is the easy part of RPM. The hard part is turning a stream of vitals into actionable clinical events without overwhelming care teams with false positives. We share the architecture pattern behind our most successful RPM deployments.
Eric Heflin
January 22, 2026
Federally Qualified Health Centers serve 30M+ Americans but are often last to receive AI-assisted diagnostics. The SafeCDx project demonstrates how point-of-care AI with FHIR-native reporting can close the diagnostic equity gap in underserved communities.
Maria Filipova
January 8, 2026
We publish technical articles from practitioners building healthcare AI. Reach out if you have a case study, tutorial, or perspective to share.