Our Approach to Health Informatics & Digital Health Systems

Designing healthcare systems with clarity, standards, and system-level thinking.

Digital health initiatives succeed only when informatics foundations—standards, interoperability, data governance, and analytics—are designed correctly. Unified Available focuses on health informatics as the backbone that enables scalable and compliant digital health systems.

Core Domains of Our Approach

Our approach integrates the key domains that determine how healthcare systems function in practice.

Clinical & Semantic Standards

Clinical data must be represented consistently to preserve meaning across care delivery, analytics, and exchange. We emphasize semantic standards that ensure clinical intent remains intact across systems.

Examples:
SNOMED CT, LOINC, RxNorm, MedDRA

Revenue, HIM & Payment Systems

Clinical data must be represented consistently to preserve meaning across care delivery, analytics, and exchange. We emphasize semantic standards that ensure clinical intent remains intact across systems.

Examples:
ICD-11, ICD-10-PCS, HCPCS, DRGs, revenue cycle workflows

Interoperability & Health Data Exchange

Modern healthcare relies on interoperable systems that exchange data securely and meaningfully across organizations and borders. Architecture matters more than formats alone.

Examples:
HL7 FHIR, C-CDA, APIs, JSON/XML/Turtle, ABDM, cross-border exchange

Data, Analytics & Intelligence

Analytics and AI depend on standardized data models and well-designed pipelines. We focus on foundations that support reliable real-world analysis and decision-making.

Examples:
OMOP, SQL, real-world data, AI/ML pipelines, cloud analytics platforms

How These Domains Work Together

Healthcare systems fail when domains are designed in isolation. Our approach emphasizes how clinical standards, revenue systems, interoperability, and analytics interact as a single ecosystem.

This system-level perspective helps professionals and organizations:

  • Design scalable digital health platforms

  • Reduce downstream integration and data failures

  • Build analytics grounded in real clinical and operational workflows

This approach informs how we structure our programs, publish insights, and support real-world system design.