Validity of Diagnostic Algorithms for Cardiovascular Diseases in Japanese Health Insurance Claims

Circ J. 2023 Mar 24;87(4):536-542. doi: 10.1253/circj.CJ-22-0566. Epub 2023 Jan 28.

Abstract

Background: We aimed to validate a claims-based diagnostic algorithm to identify hospitalized patients with acute major cardiovascular diseases (CVDs) from health insurance claims in Japan.

Methods and results: This retrospective multicenter validation study was conducted at 4 institutes, including Japanese Circulation Society-certified and uncertified hospitals in Japan. Data on patients with CVDs in departmental lists or with International Classification of Diseases, 10th Revision (ICD-10) codes for CVDs hospitalized between April 2018 and March 2019 were extracted. We examined the sensitivity and positive predictive value of a diagnostic algorithm using ICD-10 codes, medical examinations, and treatments for acute coronary syndrome (ACS), acute heart failure (HF), and acute aortic disease (AAD). We identified 409 patients with ACS (mean age 70.6 years; 24.7% female), 615 patients with acute HF (mean age 77.3 years; 46.2% female), and 122 patients with AAD (mean age 73.4 years; 36.1% female). The respective sensitivity and positive predictive value for the algorithm were 0.86 (95% confidence interval [CI] 0.82-0.89) and 0.95 (95% CI 0.92-0.97) for ACS; 0.74 (95% CI 0.70-0.77) and 0.79 (95% CI 0.76-0.83) for acute HF; and 0.86 (95% CI 0.79-0.92) and 0.83 (95% CI 0.76-0.89) for AAD.

Conclusions: The validity of the diagnostic algorithm for Japanese claims data was acceptable. Our results serve as a foundation for future studies on CVDs using nationwide administrative data.

Keywords: Acute aortic disease; Acute coronary syndrome; Acute heart failure; Claims data; Validation.

Publication types

  • Multicenter Study

MeSH terms

  • Acute Coronary Syndrome* / diagnosis
  • Aged
  • Algorithms
  • Aortic Diseases*
  • Cardiovascular Diseases* / diagnosis
  • Databases, Factual
  • East Asian People
  • Female
  • Heart Failure* / diagnosis
  • Humans
  • Insurance, Health
  • Male
  • Predictive Value of Tests