Use Case
Simplify Management and Consumption of Healthcare Data
Navigating the complexities of health insurance and patient data integration requires a unified approach. Timbr ontology based semantic layer bridges the gap by implementing FHIR (Fast Healthcare Interoperability Resources) standards as a SQL ontology that connects fragmented patient information across insurers, healthcare providers, and claims data.
This comprehensive solution enables insurers with necessary and convenient data access to provide personalized healthcare plans, optimize claims management, and ensure compliance with evolving regulations.
BEHIND THE USE CASE
The ontology-based semantic layer enables easy implementation and adoption of data architectures that leverage HL7 FHIR data definitions and ontology, to support healthcare data interoperability.
USE CASE TEMPLATE
Timbr Github repository contains a collection of SQL ontology-based semantic data models. These ontologies serve as customizable templates, designed to help users jump-start their modeling process tailored to their specific business domains.
USE CASE ONTOLOGY MODEL
The ontology semantic model makes it easy to understand and find data across tables and datasets. Timbr speeds up data discoverability by displaying data as a network and in a business-friendly manner.
REFERENCE ARCHITECTURES
Timbr embedds semantic intelligence into leading architectures including, Microsoft Fabric, Google Cloud, AWS Cloud and Snowflake.
Challenges
Struggling with Disconnected Health Data?Health insurers manage data from multiple sources, including patient claims, treatment plans, and medical records, which often exist in silos. This fragmentation prevents a full understanding of patient health, limiting the ability to offer tailored insurance plans and care strategies.
Trouble Keeping Up with Evolving Compliance Standards?Implementing and maintaining interoperability with FHIR and other healthcare standards is complex. Gaps in compliance can delay care, increase operational costs, and create inefficiencies as insurers struggle to ensure seamless communication between healthcare providers and their internal systems.
Is Data Overload Slowing Down Your Processes?The ever-growing volume of health-related data—claims, policies, patient records—overwhelms legacy systems. Insurers face the challenge of sifting through large datasets efficiently to identify insights that optimize patient outcomes, prevent fraud, and make informed underwriting decisions.
Why Timbr
Unified Data with FHIR Standardization:Timbr integrates patient data from claims, medical records, and provider systems using the FHIR standard. This seamless data integration offers insurers a 360-degree view of patient health, ensuring smoother communication and more personalized service.
Relationships Between Data for Comprehensive Insights:Timbr ontology based semantic model, enables insurers to explore patient data relationships that go beyond basic claims information, such as linking treatment patterns to risk profiles, or identifying preventive care opportunities from past medical history.
Seamless Healthcare Data Consumption:Timbr’s semantic layer allows insurers to query complex patient data directly from the source. Timbr REST API incorporates GraphQL capabilities and Semantic Swagger so users benefit from simplified data access to one or more data sources, data integration, relationships, results nesting, expressive querying and enhanced security.
Impact
Improved Patient Health Outcomes:Timbr empowers insurers to offer personalized care plans by connecting the dots across a patient’s health records and claims history, leading to better patient outcomes and more precise risk management.
Streamlined Claims Processing:By unifying patient data across multiple systems, Timbr helps insurers accelerate claims adjudication processes, reducing the time taken to process claims and improving operational efficiency.
Compliance and Regulatory Alignment:Timbr’s use of FHIR and other health insurance standards ensures that insurers remain compliant with evolving regulations while also enhancing data governance and security.
