AI-Assisted Clinical Quality Language Plugin

Simplifying clinical quality measure authoring with AI-powered code generation

A healthcare technology organization partnered with Go Brilliant to build a proof-of-concept AI plugin that converts plain English intents into valid CQL expressions, dramatically simplifying the authoring process for clinical quality measures.

Client Profile

A healthcare organization focused on clinical quality measurement, working with clinical teams to author and validate complex quality measures using Clinical Quality Language (CQL).

The Challenge

Clinical teams faced significant obstacles when working with CQL:

Complex Syntax: CQL's formal syntax proved challenging for clinical professionals without programming backgrounds
Time-Intensive Authoring: Writing and debugging CQL expressions consumed significant time for quality measure authors
Error-Prone Process: Manual coding led to frequent syntax errors and logical mistakes requiring extensive review
Limited Accessibility: The technical barrier limited who could effectively contribute to quality measure development
Validation Challenges: Ensuring expression correctness required deep CQL expertise and testing

Our Solution

Go Brilliant built an innovative AI-assisted plugin that bridges the gap between clinical intent and CQL code:

AI-Powered Conversion Pipeline

Natural Language Processing: Advanced LLM-based understanding of clinical intent expressed in plain English
Intent to Structure: Conversion of natural language into intermediate JSON representation capturing logic
CQL Generation: Transformation of structured intent into valid, syntactically correct CQL expressions
Real-Time Validation: Automatic syntax checking and validation against CQL specifications
Suggestion Engine: Intelligent recommendations for corrections and improvements
Context Awareness: Understanding of common clinical patterns and measure structures

Plugin Features

Intuitive interface for entering clinical intent in natural language
Live preview of generated CQL with syntax highlighting
Real-time linting and error detection with explanatory messages
Side-by-side view of natural language input and CQL output
Export functionality for integration with existing CQL development tools

Implementation Approach

Designed sophisticated prompt templates for LLM-based CQL generation with clinical context
Implemented English → JSON → CQL conversion pipeline with validation at each stage
Integrated plugin features including preview, linting, and intelligent syntax suggestions
Validated generated expressions against real clinical quality measure use cases
Conducted iterative testing with clinical quality measure authors

Technology Stack

OpenAI GPT for natural language understanding, TypeScript for plugin development, Node.js for backend processing, and integration with CQL IDE framework for development environment.

         Results & Impact
        Reduced Authoring Time: AI-assisted generation significantly accelerated CQL expression development
Fewer Syntax Errors: Automated generation and validation dramatically reduced coding mistakes
Proven Concept: Successfully demonstrated viable natural-language-to-CQL workflow for clinical teams
Improved Accessibility: Lowered technical barrier for clinical professionals to work with CQL
Enhanced Efficiency: Quality measure authors could focus on clinical logic rather than syntax

      

Key Highlights

Innovative application of large language models to clinical quality measurement
Multi-stage conversion pipeline ensuring accuracy and validity
Real-time feedback and validation improving user experience
Extensible architecture supporting future enhancements and features
Proof-of-concept demonstrating transformative potential for CQL authoring workflows

"Go Brilliant delivered exceptional results with speed, quality, and innovation. The AI-assisted CQL plugin demonstrated how AI can transform clinical quality measure development, making it more accessible and efficient."

— Clinical Quality Director, Healthcare Technology Organization

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