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Unlocking the Power of FHIR for AI-Driven Oncology

•By Srotas Team
Unlocking the Power of FHIR for AI-Driven Oncology

How Srotas Health is reimagining clinical decision-making with seamless, standards based integration.

As an oncologist, few decisions are as time sensitive and high stakes as matching a patient to a clinical trial. Yet, this process is often delayed by disconnected systems and incomplete data.

At Srotas Health , we’re building an AI powered oncology platform that turns this challenge into an opportunity by putting FHIR (Fast Healthcare Interoperability Resources) at the heart of our architecture.

FHIR allows us to connect deeply with hospital systems, enabling real time, secure, and compliant access to clinical data, the key to unlocking AI’s full potential in oncology.

Why FHIR? Why Now?

FHIR is rapidly becoming the standard language of modern healthcare. Created by HL7, it’s designed for interoperability, scalability, and compliance.

Here’s why it works for us:

  • Interoperability: Structured data exchange across EHRs, labs, and imaging
  • Security: Built in support for HIPAA/GDPR compliance
  • Adoption Ready: Already supported by EHRs like Epic, Cerner, and Allscripts

How Srotas Health Uses FHIR to Power AI in Oncology

At Srotas Health, we believe that AI should work with clinicians, not around them. That’s why we’ve architected our platform around FHIR enabling seamless, secure, and scalable integration with hospital systems. From data ingestion to intelligent decision making, every component in our pipeline is designed to deliver real-time, explainable insights right where care happens.

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1. Seamless FHIR Integration:

We integrate with partner hospitals through secure FHIR REST APIs, often via SMART on FHIR apps:

  • OAuth2 for authentication

  • Scoped access to required data fields

  • All connections are encrypted, audited, and governed by data sharing agreements

2. Summarization with LLMs:

Once data is ingested:

  • FHIR bundles (patient records, encounters, labs) are parsed and grouped
  • We use LLM to generate structured summaries
  • These are converted into validated JSON schemas, machine readable and ready for downstream use.

3. Smart Search via Embeddings:

All summaries are indexed in a vector database, enabling:

  • Semantic, context aware search
  • Fast patient trial matching
  • Flexible querying by clinicians and coordinators

4. Intelligent, Explainable AI:

Using a combination of metadata filtering, semantic search, and LLM reasoning, we:

  • Surface eligible patients for clinical trials
  • Provide structured, explainable results
  • Show both matches and non matches with reasons behind each

5. Embedded in Clinical Workflows:

Our outputs are integrated directly back into the EHR with:

  • Role based views (clinicians, researchers, data managers)
  • Real time alerts

No extra tools. No disruption. Just insight where it’s needed.

What’s Next in AI Oncology

  • Genomics Integration: Using FHIR Genomics standards to bring in NGS data and support mutation based trial matching.
  • Trial Feasibility Forecasting: Leveraging real world EHR data to help sponsors and hospitals predict enrollment timelines and optimize inclusion criteria.
  • Enabling Decentralized Trials: By combining FHIR with remote monitoring capabilities, we’re enabling a new era of decentralized clinical trials. This approach allows us to conduct virtual eligibility assessments, support site less participation for patients regardless of location, and automatically sync follow up data back into electronic health records in real time, making trials more accessible, efficient, and patient centric.

Conclusion

Before FHIR, too much of oncology decision making relied on disconnected data, incomplete histories, and missed opportunities. At Srotas Health , we’re changing that narrative.

By combining the interoperability of FHIR with the power of AI, we’re transforming oncology into a discipline of real time, intelligent, and clinician aligned decision making. Our modular, vendor agnostic architecture means that what works in one hospital can scale to many , unlocking AI for every patient, every trial, every time.

This isn’t just a digital upgrade. This is augmented oncology where insight meets action.

At Srotas Health, we’re committed to leveraging AI innovations that streamline clinical research. By implementing AI-driven site identification, sponsors and CROs can optimise trial performance paving the way for more rapid, cost-effective, and patient-centric clinical studies.

Authored by : Dr Heeba Altaf Ramji Balasubramanian Vikram Parimi Suman Bhaskaran

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