Engineering teams that understand clinical reality
Healthcare — Hospitals & Health Systems
What the compliance landscape actually demands.
Health systems operate under a regulatory architecture that most technology vendors have never read in full. HIPAA's Security Rule mandates technical safeguards at the infrastructure layer — access controls enforcing the minimum necessary standard, audit controls generating records sufficient for forensic review, transmission security encrypting PHI in motion and at rest. These are engineering requirements, not policy statements. A system that satisfies the documentation but fails to implement the safeguards is not HIPAA-compliant regardless of what the BAA says. The ONC information blocking rule adds a second compliance surface: covered entities that restrict access to EHI without a permitted exception are subject to civil monetary penalties that can reach $1M per information blocking practice. FHIR R4 interoperability mandates mean that every clinical system must expose standardized APIs — and every API endpoint that surfaces PHI is a new HIPAA scope boundary requiring documented controls. Epic and Cerner integration complexity compounds the challenge: HL7 v2 interfaces, FHIR adapters, and custom integration engines each represent distinct data flows requiring separate access control and audit documentation. At the AI layer, NIST AI RMF is emerging as the governance standard — requiring model documentation, bias testing, and ongoing monitoring that the vast majority of healthcare AI systems do not currently satisfy.
Every AI system touching patient data creates a HIPAA audit surface that most vendors don't map until it's too late.
Health systems operate under the most demanding regulatory environment in technology. Every system touching patient data must be HIPAA-compliant at the architecture level. The incumbents treat compliance as a Phase 3 conversation. By then, the architecture is locked and remediation costs 3x the original build.
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The EHR duopoly — Epic at approximately 38% of US hospital beds, Oracle Health (Cerner) covering most of the remainder — shapes every integration decision a health system makes. Both platforms were architected before FHIR was a standard, before cloud-native infrastructure was viable for clinical workloads, and before AI-assisted care was a clinical reality. Every application that requires patient data must negotiate Epic's App Orchard or Cerner's code program, accept their API rate limits, and operate within their data governance framework. A single HL7 interface that exposes PHI to an analytics platform without explicit BAA coverage and access logging creates a HIPAA violation that compliance teams typically discover during their annual audit — not in real time. The vendors who built the healthcare IT market — Cognizant, Optum, Leidos — don't bear the regulatory consequences when their integrations fail. The health system does. Cognizant's 2020 ransomware attack cost the company $50–70M and disrupted care delivery across their client base. The Change Healthcare ransomware attack in 2024 disabled claims processing for thousands of providers and exposed over 100 million patient records — and the investigation continues to reveal that architecture decisions made years earlier created the blast radius.
How We Approach Hospitals & Health Systems
The Algorithm approaches health system engagements with compliance architecture as the first deliverable, not the last. Before any code is written, our engineers map the data flows, identify every PHI touchpoint, document the HIPAA technical safeguard implementation for each system boundary, and produce the architecture documentation that will satisfy the OCR audit if one occurs. Epic and Cerner integrations are designed from the interface layer with FHIR-native data exchange, SMART on FHIR authentication, and audit logging that captures every PHI access event with sufficient detail for forensic review. HITRUST CSF controls are mapped to infrastructure decisions — not retrofitted through a compliance questionnaire after the system is built. For health systems deploying AI-assisted clinical tools, we implement the NIST AI RMF documentation and monitoring requirements as part of the build — model cards, bias test results, performance monitoring pipelines, and the governance documentation that the compliance committee needs to approve production deployment. The result is a system that passes HIPAA audit on day one, satisfies information blocking requirements by design, and can demonstrate ONC certification readiness without an emergency remediation engagement.
What Success Looks Like
A successful engagement delivers a production system that passes HIPAA technical safeguard review before it processes its first patient record. Epic or Cerner integration is FHIR-native with audit logging that satisfies ONC information blocking documentation requirements. AI components have NIST AI RMF documentation packages ready for compliance committee review. The clinical staff can use the system without workarounds. The compliance team can document it without reconstructing access logs. The security team can verify every safeguard without a manual audit exercise. The health system owns the architecture and can maintain it without a vendor on retainer.
Duration: 8 - 16 weeks
Output: Production system + audit documentation
A regional health system replacing a failed EHR implementation typically engages at Tier I — 20 engineers, 12 weeks, production-ready.
What We Deploy in Hospitals & Health Systems
Healthcare — Hospitals & Health Systems Compliance Assessment
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