EXECUTIVE SUMMARY
In healthcare, unstructured data from various sources like clinical documents, lab reports, and
EHRs (Electronic Health Records) make data integration and interoperability a significant
challenge. Trove Health’s Trident AI presents an innovative solution to this problem by
automating the conversion of unstructured data into structured and cleaned formats, such as
FHIR R4, enabling its use in a wide range of healthcare applications. With its ability to parse over
95% of data with 97% accuracy, Trident AI drives significant savings and operational efficiencies
across healthcare use cases, from patient management to clinical research.
INTRODUCTION: THE NEED FOR STRUCTURED DATA IN HEALTHCARE
Healthcare generates vast amounts of unstructured data daily in CCDA (Consolidated Clinical
Document Architecture) files, PDFs, and other formats. This data is critical for improving patient
outcomes, clinical research, and operational efficiency, but it is locked under challenging
formats to parse and integrate. By converting unstructured data into structured formats like
FHIR R4, healthcare organisations can unlock their full potential, allowing for better
interoperability, clinical decision support, and data-driven insights. Trove Health’s Trident AI
offers an advanced solution for converting, parsing, and structuring healthcare data at scale,
ensuring accuracy and usability.
TRIDENT AI CAPABILITIES FOR DATA STRUCTURING
1. TAKING IN CCDA FILES AND CONVERTING TO FHIR R4
Trident AI can seamlessly ingest CCDA files in XML format and convert them into the industry-
standard FHIR R4 format. FHIR (Fast Healthcare Interoperability Resources) R4 is increasingly
adopted as the standard format for healthcare data exchange, making it easier for different
healthcare systems to share and interpret patient information.
2. REAL-TIME PARSING OF CCDA FILES
In addition to converting CCDA files, Trident AI can parse them in real time. This feature is
critical for time-sensitive applications, such as emergency care, where rapid access to structured
data can improve clinical outcomes.
3. HIGH DATA ACCURACY AND COVERAGE
Trident AI can parse over 95% of the data with more than 97% statistical accuracy. This high
level of accuracy is essential for healthcare use cases where even minor errors in patient data
can lead to significant clinical implications.
4. PARSING HUMAN-READABLE SECTIONS INTO STRUCTURED FORMATS
Many CCDA files contain human-readable sections that are difficult for machines to interpret.
Trident AI excels at converting these human-readable portions into structured formats, making
it easier for healthcare providers to analyse and act on the data.
KEY USE CASES FOR STRUCTURED DATA IN HEALTHCARE
1. IMPROVED CLINICAL DECISION MAKING
Trident AI enables healthcare providers to access comprehensive patient information quickly
and accurately by converting unstructured data into standardised, structured formats. This
improved data accessibility can lead to more informed clinical decisions, reduce errors, and
improve patient outcomes.
Example: Studies have shown that data-driven clinical decision-support tools can reduce medical
errors by 25%, leading to significant cost savings and improved patient care1
2. BETTER POPULATION HEALTH MANAGEMENT
Structured data allows healthcare organisations to analyse population health trends and
intervene proactively. Trident AI's ability to parse and structure large volumes of data enables
healthcare providers to manage chronic diseases more effectively and implement targeted
interventions for at-risk populations.
Example: According to CDC reports, population health management powered by structured data
can reduce healthcare costs associated with chronic conditions by up to 15%2
3. ENHANCED INTEROPERABILITY
Interoperability is one of the biggest challenges in healthcare, as different systems often use
incompatible data formats. By converting CCDA files into FHIR R4, Trident AI ensures that
patient data is easily shareable across systems, improving care coordination and reducing
duplication of services.
4. ACCELERATING CLINICAL RESEARCH
Clinical research relies heavily on structured, accurate data. By automating Trident AI data
structuring, researchers can gain faster access to clean, usable data for studies and trials. This
accelerates the research process and lowers costs.
Example: Automating data structuring in clinical trials can cut research timelines by 20%, leading
to significant cost reductions and faster treatment delivery to market3
CONCLUSION
Trove Health’s Trident AI offers healthcare providers, researchers, and administrators a
powerful solution to unstructured data challenges. By converting CCDA files into structured
formats like FHIR R4, parsing data in real-time, and ensuring high accuracy, Trident AI creates
clean, actionable data that drives better decision-making, improves patient outcomes, and
lowers healthcare costs. With potential savings of up to 20% across various healthcare use
cases, Trident AI is a critical tool for any healthcare organisation looking to leverage AI and data
for better outcomes.
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