Self-serve claims analytics

A calm, governed workbench for claims evidence

CME helps life-sciences teams turn healthcare claims data into reproducible cohorts and answers — across Oncology, Hematology, and Autoimmune therapeutic areas — without waiting on a data engineering queue.

Explore the workbench Request access
  • Oncology, Hematology & Autoimmune
  • Reproducible cohort logic
  • Manifest-bounded querying
  • Governed data sources
Stylized illustration of the Claims Modular Engine analytics workbench

The workbench

Everything a claims study needs, in one place

Five connected modules take you from raw claims sources to defensible evidence — each designed to keep cohort logic transparent and reusable.

Data Library

Governed claims datasets, ready to analyze

Browse and connect curated claims datasets in one place. Each source is described with its coverage, vintage, and lineage so analysts start from trusted, well-understood data.

Projects

Configure a cohort study, step by step

A guided wizard walks you from disease and drug definition through scope, datasets, code discovery, rule vetting, and module selection. Every choice is captured so the analysis is reproducible.

Code Library

Reusable, version-aware code lists

Discover, subscribe to, and track updates on diagnosis and procedure code sets. Keep cohort definitions consistent across projects and stay current as code lists evolve.

Vibe Studio

Ask your cohort questions in plain language

A manifest-bounded Text-to-SQL studio over your project's Intermediate Tables. Ask about lines of therapy, regimens, or comorbidities and get answers safely scoped to your project.

Agents

Automate recurring analyses

Production agents run recurring cohort summaries, scheduled queries with alerting, and product-KPI monitoring — so routine reporting happens on its own.

How it works

Configure a study, step by step

The project wizard captures every decision so your analysis is transparent and reproducible from definition to run.

  1. 01

    Define disease & drug

    Frame the question

    Set the therapeutic area, condition, and product of interest to anchor the study.

  2. 02

    Set scope

    Population & timeframe

    Establish the index period, inclusion windows, and the population the analysis should cover.

  3. 03

    Choose datasets

    Connect the data

    Select the governed claims sources that feed the cohort from the Data Library.

  4. 04

    Discover codes

    Build the definitions

    Surface candidate diagnosis and procedure codes and assemble the lists that define your cohort.

  5. 05

    Vet rules

    Review & refine

    Inspect and adjust the cohort logic so every inclusion and exclusion rule is intentional.

  6. 06

    Select modules & run

    Produce evidence

    Pick the analytic modules to compute, then run the project to generate cohort tables and outputs.

Governed by design

Querying is manifest-bounded and scoped to your project's Intermediate Tables, so analysts explore freely within guardrails that keep data access controlled.

Modular & reproducible

Reusable code lists and captured cohort logic mean studies can be re-run, audited, and shared across teams without rebuilding definitions each time.

Ready to put your claims data to work?

Access is by invitation. Sign in with your account, or reach out to request one for your team.

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