Operationalizing an AI-driven clinical decision support system for early diagnosis

AI holds immense promise in clinical care, but realizing that promise requires more than a powerful algorithm. It takes the right platform, integrated workflows, and robust compliance.

A leading US-based medical technology company, known for its hematology analyzers and FDA-certified Early Sepsis Indicators, had developed a breakthrough: an AI/ML model to detect sepsis risk early and aid in timely clinical intervention.

The next step? Operationalizing it at scale. That’s where CitiusTech stepped in.

The Challenge: Turning predictive AI into a clinical workflow

With the sepsis detection algorithm ready, the client’s focus shifted to implementation. They needed to embed intelligence into the clinical environment securely, reliably, and seamlessly.

Their vision required:

• A scalable digital platform that could host current and future CDSS tools.
  
  
• Integration with existing EHR systems to ensure frictionless data flow.
  
  
• A specialized module to evaluate 30-day MACE (Major Adverse Cardiac Events) risk.
  
  
• Real-time access to lab results, vitals, and evolving risk scores.
  
  
• End-to-end data privacy and regulatory compliance.

While the algorithm had clinical potential, its success hinged on delivering it through a robust, connected, and clinician-friendly system.

The Solution: A cloud-based, multitenant CDSS platform

Collaborated with the client to design and develop a multi-tenant cloud-based Clinical Decision Support System, a centralized platform engineered to scale. Key features of the solution included:

• Uniform enforcement of privacy, security, and compliance protocols. Secure account, access, and configuration management with efficient logging, tracing, monitoring, and deidentification functionalities.
  
  
• Seamless EHR system integration, using Mirth Connect for reliable HL7 and FHIR connectivity.
  
  
• A cutting-edge SMART-on-FHIR app with an intuitive and responsive interface for clinical decision support.
  
  
• Advanced AI models for myocardial infarction risk assessment, leveraging Azure’s MLOps pipeline for real-time, accurate risk scoring.
  
  
• Centralized management for rapid updates and clinical algorithm improvements.
  
  
• Seamless integration with hospital EHR systems to support point-of-care insights.
  
  
• Reusable microservices to accelerate the deployment of future CDS applications.
  
  
• Full-stack support for monitoring, operations, and analytics.

The developed digital platform featured a flexible, user-friendly, centralized, and scalable design, complete with dashboards, snapshots, lab result tracking, and trend analysis for comprehensive analytics, enhancing patient care.

The Results: Real-time insights, rapid deployment, and scalable impact

The collaboration delivered measurable value to both the client and their healthcare partners:

• Efficient, scalable digital foundation for all clinical decision support applications.
  
  
• Standardized integrations enabling shared data and configuration across hospitals.
  
  
• Faster application rollouts through reusable components and prebuilt services.
  
  
• Enhanced visibility and control via a comprehensive monitoring and support platform.
  
  
• Cost savings through centralized management and reduced development effort.
  
  

With CitiusTech’s support, the client brought their AI algorithm to life, enabling real-time clinical decisions and redefining their competitive edge in the MedTech market.