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.
