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The Claims Data Learning & Enhancing for Algorithm Refinement (CLEAR) Study: Overview of the Study Design and

Haruhisa Fukuda1, Megumi Maeda1, Chieko Ishiguro2

  • 1Department of Health Care Administration and Management, Kyushu University Graduate School of Medical Sciences.

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|December 7, 2025
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Summary

The CLEAR Study platform in Japan links medical claims with diagnostic data to validate disease identification algorithms. This improves the reliability of epidemiological studies and drug risk assessments using claims data.

Keywords:
Japanadministrative datadiagnostic datadisease identification algorithmsvalidation studies

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Area of Science:

  • Health Informatics
  • Epidemiology
  • Data Science

Background:

  • Medical claims data are crucial for epidemiological studies but often lack sufficient validation for disease identification accuracy.
  • Existing validation methods for claims data can be costly and time-consuming.

Purpose of the Study:

  • To introduce the Claims data Learning & Enhancing for Algorithm Refinement (CLEAR) Study, a novel database platform in Japan.
  • To enable systematic, low-cost validation of algorithms used for identifying diseases in medical claims data.

Main Methods:

  • The CLEAR Study platform links patient-level medical claims data with diagnostic data (e.g., lab results, imaging reports) serving as the gold standard.
  • Data linkage is achieved using pseudonymized medical record numbers, with personal information protected by research identification numbers.
  • The platform's feasibility was demonstrated using data from respiratory syncytial virus (RSV) infections and intussusception cases.

Main Results:

  • Eight hospitals joined the CLEAR Study, with three already providing claims data.
  • Data were collected for 5,022 RSV infection cases and 1,450 intussusception cases.
  • Initial analysis of diagnostic data for tens of thousands of cases confirmed the database's utility for algorithm validation.

Conclusions:

  • The CLEAR Study platform facilitates crucial validation of medical claims data in Japan.
  • By enhancing the reliability of claims-based research, the platform supports more accurate epidemiological studies and drug risk assessments.