AI-Powered Oncology Platform for Personalized Cancer Care

Digital Health

Client Background.

A specialty oncology-focused digital health company aimed to develop an AI-powered, FHIR-compliant cancer care platform to help oncologists track patient progression, optimize treatment decisions, and improve survival rates.

Business Problem.

  • Fragmented Oncology Data – EHRs stored unstructured & incomplete oncology-specific data, making it hard to extract insights.
  • Lack of Standardized Cancer Progression Metrics – No automated way to track disease stages, therapy responses, and patient outcomes in real time.
  • Limited Patient Engagement & Survivorship Tracking – Cancer patients lacked structured post-treatment monitoring & real-time risk assessment.
  • Manual Tumor Board Coordination – Oncologists had to manually compile data for multidisciplinary tumor boards, delaying treatment decisions.

Our Solution.

  • Developed a FHIR-Enabled Oncology Data Aggregation Platform – Integrated oncology-specific FHIR resources (Observation, Condition, Medication Request, Diagnostic Report, Procedure) to streamline cancer care.
  • AI-Powered Cancer Progression & Prognostic Modeling – Built machine learning models that analyze tumor size, biomarker trends, and lab results to predict treatment responses.
  • Automated Tumor Board Coordination System – Created a cloud-based tumor board platform where oncologists can collaborate in real-time, access AI-driven insights, and standardize decision-making.
  • Survivorship & Remote Monitoring – Built patient engagement apps with personalized post-treatment care plans, AI-driven symptom tracking, and virtual follow-ups.

Implementation Process.

  • Month 1: FHIR-based oncology data ingestion & integration with hospital EHRs.
  • Month 2: AI model development for cancer progression analysis & treatment recommendations.
  • Month 3: Tumor board automation, clinician dashboard, and reporting engine.
  • Month 4: Deployment of patient engagement features & remote monitoring tools.

Results & Impact.

  • 35% Faster Tumor Board Decision-Making – AI-assisted clinical insights reduced the time required for treatment planning.
  • 50% Improvement in Post-Treatment Adherence – Survivorship programs increased patient follow-up rates and symptom tracking.
  • Real-Time Cancer Progression Monitoring – AI-driven analytics helped oncologists identify high-risk patients earlier.
  • FHIR-Based Data Standardization Across Hospitals – Enabled seamless oncology data exchange between research institutes, hospitals, and payors.

Key Takeaways.

  • FHIR-based oncology platforms improve cancer data standardization & interoperability.
  • AI-driven prognostic modeling enhances treatment decision-making.
  • Automated tumor board solutions improve multidisciplinary collaboration & efficiency.
  • Patient engagement through AI-powered tracking improves long-term cancer care outcomes.