Healthcare data standardisation and interoperability.
4 projects
An online filing and data-management system built for hospitals, integrating patient demographics, physician/clinic details, diagnosis and cancer staging, structured exams and imaging reports, malignancy-renewal assessment forms and chart attachments — with a RESTful API and JSON payload preview for a one-stop electronic workflow for catastrophic-illness applications.
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A next-generation healthcare data platform built on the HL7® FHIR® (Fast Healthcare Interoperability Resources) international standard. Through a standardized data model and microservices architecture, it connects and integrates heterogeneous in-hospital systems downstream (HIS, LIS, PACS, NIS, EMR and wearable devices), cleansing, transforming and mapping multi-source, proprietary-format data into standardized FHIR Resources (Patient, Observation, Condition, Encounter, etc.); upstream, it provides a unified, secure RESTful API, a SMART on FHIR authorization framework and event-driven services, acting as the hospital's data hub and fully supporting clinical decision-making, AI deployment and cross-institution interoperability.
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A next-generation full-lifecycle health-indicator tracking and smart-alert platform that fuses the HL7 FHIR international standard with clinical logic (CQL). It's designed to break past the limits of traditional health data — "only a snapshot value, no dynamic tracking" — by automatically capturing and linking longitudinal vitals, lab reports and clinical indicators through a standardized interface. Built-in dynamic traffic-light risk grading and clinical rules automatically compare, trend and stratify results, closing the loop from everyday self-managed health to early clinical intervention.
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A highly flexible, extensible FHIR Implementation Guide (IG) conversion engine that solves the classic healthcare-integration pain point of "varied source formats, shifting standard versions." It accepts diverse data sources (HL7 v2 messages, hospital-specific formats, CSV/Excel files, SQL query results, or custom JSON/XML) and, through visual or declarative mapping rules, precisely cleanses, aligns and converts data into FHIR Profiles/IGs that meet specific international or local requirements (such as Taiwan's TW Core IG). A built-in automated semantic-validation mechanism ensures output resources fully comply with each IG's constraints and code-system rules.
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