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Development and Validation of a Claims-Based Algorithm for Identifying Incident Colorectal Cancer and Determining

Nobukazu Agatsuma1,2,3, Takahiro Utsumi1, Takahiro Inoue1

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A new algorithm accurately identifies colorectal cancer (CRC) cases and their progression phases using health insurance claims. This tool aids research into real-world CRC practices and healthcare costs.

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Area of Science:

  • Health Services Research
  • Oncology
  • Medical Informatics

Background:

  • Health insurance claims provide valuable data on clinical practice and costs.
  • Inaccurate diagnosis codes and lack of staging in claims limit understanding of colorectal cancer (CRC) clinical practice.
  • Accurate identification of CRC cases and progression is crucial for research.

Purpose of the Study:

  • To develop and validate an algorithm for accurately identifying incident colorectal cancer (CRC) cases using claims data.
  • To classify CRC patients into distinct progression phases based on treatment sequences.
  • To improve the understanding of CRC clinical practice and associated healthcare costs through claims data analysis.

Main Methods:

  • Retrospective study using claims data from three Japanese institutions (April 2016 - August 2022).
  • Developed an algorithm using CRC diagnostic and treatment codes to identify incident cases and classify progression phases (endoscopic, surgical, noncurative).
  • Refined and validated the algorithm using cohorts from designated cancer care hospitals (DCCHs) to enhance performance metrics like positive predictive value (PPV) and sensitivity.

Main Results:

  • The algorithm achieved high performance metrics after enhancements, including filtering prevalent cases and targeting invasive CRC.
  • Positive predictive values (PPVs) for incident invasive CRC were 91.2% and 94.4%.
  • Sensitivities reached 94.6% and 100.0%, with progression phase accuracies of 91.5% and 97.6% in validation cohorts.

Conclusions:

  • The developed algorithm accurately identifies incident invasive colorectal cancer (CRC) cases and their progression phases from claims data.
  • This validated algorithm can significantly contribute to research on real-world CRC clinical practices.
  • The tool facilitates better analysis of medical care costs associated with colorectal cancer.