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Solution Accelerators

Pre-built solutions, code samples, and reference implementations to help you quickly integrate IMO Health’s clinical intelligence into your applications.

Each accelerator includes production-ready code, deployment guides, and best practices.

Ambient Listening

Python · REST API — Convert medical transcripts into structured clinical data. Uses Entity Extraction, Precision Normalize, and Search & Capture to turn patient-provider conversations into SOAP notes, then extract, normalize, and code clinical entities.

Real-time entity extraction · Normalization with enrichment · Automated clinical coding

Real World Evidence

Python · REST API — Transform raw clinical data into clean, standardized OMOP-ready datasets and precisely targeted patient cohorts using Precision Normalize and Precision Set.

IMO API integration · OMOP-ready output · Multi-source data support · Data lake integration

Coding Intelligence

Python — Validate every diagnosis code against real-world billing rules, flagging unspecified laterality, non-primary diagnoses, and CMS Excludes1 conflicts as they’re entered.

Real-time code validation · Billing accuracy checks · Multi-code system support

Clinical NLP

Python · REST API — Turn unstructured clinical notes into an organised, de-duplicated problem list. Identifies coded entities, groups them by specialty, and flags duplicates, related conditions, and lapsed problems.

Precision Normalize with Cohorting

Python · REST API — Build reproducible patient cohorts from raw clinical terminology. Standardizes terms to IMO lexical codes and FHIR-compliant terminologies, applies inclusion/exclusion value set criteria, and exports a matched cohort.

Precision Normalize with Enrichment

Python · REST API — Submit clinical terms alongside contextual metadata and get richer, more precise normalized mappings — ideal for refining ambiguous terms before cohort building or coding workflows.

Search and Capture

Python · REST API — The full clinical coding lifecycle, from interactive term search and specialty grouping through duplicate detection and ICD-10-CM coding rule validation.

Knowledge Graph Traversal

Python · GraphQL API — Walk from a raw lexical code to a fully navigated concept hierarchy. Query code system mappings and surface the specificity that unspecified codes leave on the table.

MCP Server through Databricks

MCP · Databricks Marketplace — Build an AI-powered diagnostic specificity agent using Databricks and IMO Health’s MCP Server, with a step-by-step guide to creating, deploying, and publishing an IMO-enabled agent.

MCP Server through Microsoft Copilot Studio

MCP · Microsoft Copilot Studio · Low code — Create an IMO-enabled agent that analyzes clinical documentation, identifies opportunities for diagnosis refinement, and guides users toward greater specificity.

Build with the SDKs

Several accelerators above call Precision Normalize directly over REST. In this portal that API also ships as generated clients, so the same workflows can be written in idiomatic TypeScript, Python, or Java with authentication and token refresh handled for you.