Healthcare Technology Leadership
Health plan operations, HIPAA compliance architecture, and applied AI — from an enterprise architect who has worked inside two Fortune 500 health insurance organizations and built HIPAA-compliant claims processing systems from the ground up.
Healthcare technology is governed by constraints that most industries never encounter: HIPAA compliance, PHI data handling, EDI transaction standards, and the operational reality that system failures affect patient care. Building and leading technology in this environment requires direct experience — not just general engineering skill applied to a new domain.
- Fortune 500 #204
- Large-scale platform initiative
- Enterprise architecture standards
- Complex subsidiary structure
- Fortune 500 #169
- One of the country's largest HMOs
- Health plan enterprise architecture
- HIPAA ANSI 837 / 835 / 997
- BizTalk EDI orchestration
- Claims processing pipeline
- Payer–clearinghouse integration
Enterprise architecture inside the largest health insurers
WellPoint (now Anthem) was Fortune 500 #204 when the engagement ran — one of the largest health insurance organizations in the United States. As a technology consultant, the work centered on solution architecture for a large-scale platform initiative: improving their existing complex and multifacted reporting models and establishing the architectural patterns that would govern platform evolution across a complex subsidiary structure.
A parallel engagement at PacifiCare Health Systems (Fortune 500 #169, one of the country's largest HMOs) addressed similar enterprise architecture challenges at the health plan layer. These engagements built direct familiarity with the governance, compliance, and technical complexity that defines health plan infrastructure at scale.
EDI claims integration built to HIPAA transaction standards
At HBSGI, a healthcare benefits company, the engagement covered BizTalk EDI orchestration and full HIPAA ANSI claims processing: 837 professional and institutional claim submission, 835 electronic remittance advice, and 997 functional acknowledgment. This is the integration fabric that connects providers, payers, and clearinghouses — and it carries the full weight of HIPAA compliance requirements at every transaction boundary.
Healthcare data integration at this level requires understanding both the technical EDI standards and the business rules that govern claim adjudication, remittance processing, and rejection handling. Building it correctly the first time is materially less expensive than rebuilding it after a compliance audit or a revenue cycle disruption.
Healthcare AI is not a general technology problem with a healthcare skin on it. The compliance constraints, the sensitivity of the data, and the stakes of an incorrect recommendation are categorically different from other domains. You cannot apply generic AI implementation patterns and expect them to hold.
Healthcare technology capabilities
HIPAA Architecture & Compliance
PHI data handling, HIPAA ANSI 837/835/997 transaction sets, audit logging, access controls, and the end-to-end compliance architecture that health plan operations depend on.
EDI Claims Integration
BizTalk EDI orchestration, HIPAA ANSI 835/837/997 claims processing pipelines, clearinghouse connectivity, and the healthcare data integration patterns that keep revenue cycles running.
Health Plan Enterprise Systems
Enterprise architecture for large-scale health plans and HMOs — member management, benefits administration, provider network systems, and the integration fabric that ties them together.
Care Management Technology
Platform architecture for care coordination, utilization management, prior authorization workflows, and the member-facing systems that health plan operations require at scale.
AI in Healthcare
Clinical documentation automation, prior authorization AI, care gap analysis, and population health ML — applied AI that operates within HIPAA boundaries and produces measurable clinical outcomes.
Data Governance & PHI Controls
Data classification frameworks, PHI inventory and lineage, de-identification pipelines, and the governance structures that allow health organizations to use data assets without regulatory exposure.
"Our industry of insurance is heavily regulated — Shawn Livermore understood that and delivered a powerful, secure, and compliant app."
Applied AI that operates within HIPAA boundaries
Healthcare AI is not a general-purpose problem. The same AI techniques that work in other industries require significant adaptation when PHI is involved — data handling, model training practices, output auditing, and the governance structures that allow clinical staff to trust automated recommendations. Getting this wrong creates HIPAA exposure; getting it right creates measurable clinical and operational value.
Current healthcare AI applications span clinical documentation automation (reducing physician administrative burden), prior authorization workflow acceleration, care gap identification from claims and clinical data, and population health analytics. Each requires a Chief AI Officer who understands both the technical architecture and the regulatory environment the system must operate in.
As a Fractional CAIO for healthcare organizations, the work covers AI strategy, model selection, HIPAA-aligned data governance, and the organizational change management that determines whether AI investments reach clinical use. Start the conversation.
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Enterprise architecture experience at Fortune 500 health plans, HIPAA claims processing, and applied AI within compliance boundaries — brought to your organization without a full-time executive commitment.
