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Background <p>Estimating disease epidemiology using health insurance claims data is challenging due to the lack of specific diagnostic codes. This study demonstrates an approach to estimate the epidemiology of primary immunoglobulin A nephropathy (IgAN) using German Statutory Health Insurance (SHI) claims data.</p> Methods <p>A retrospective observational study was conducted using data from January 1<sup>st</sup>, 2015 to December 31<sup>st</sup>, 2022. Two coding algorithms – one restrictive and one inclusive – were developed to identify primary IgAN cases based on ICD-10-GM codes. The restrictive algorithm identified cases based on histologically confirmed diagnoses, while the inclusive algorithm included a broader range of related diagnoses. Annual incidence and prevalence rates were calculated and extrapolated to the German population.</p> Results <p>The mean prevalence rate from 2017–2022 ranged from 4.5 (restrictive codes) to 38.3 (inclusive codes) cases per 100,000 individuals, demonstrating the orphan nature of primary IgAN. Mean incidence rates ranged from 0.2 to 0.6 cases per 100,000 individuals. In 2022, this corresponded to an estimated 4,043 to 32,229 prevalent cases and 164 to 538 incident cases in Germany.</p> Conclusion <p>This study presents an approach for estimating disease epidemiology in the absence of specific diagnostic codes, using primary IgAN as an example. While our dual-algorithm method provides valuable insights into the incidence and prevalence of primary IgAN in Germany, it also highlights the need for consistent coding practices and specific diagnostic codes for accurate epidemiological assessments.</p>

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Dilemma of missing specific disease codes: an approach to assess the incidence and prevalence of a rare nephrology disease

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月3日

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  • Matthias Roll,
  • Amadeus Gladbach,
  • Isabella Selinger,
  • Thomas Hardt,
  • Helena Himmelhaus,
  • Christian Jacob,
  • Timotheus Stremel,
  • Julia Theil,
  • Jürgen Floege

摘要

Background

Estimating disease epidemiology using health insurance claims data is challenging due to the lack of specific diagnostic codes. This study demonstrates an approach to estimate the epidemiology of primary immunoglobulin A nephropathy (IgAN) using German Statutory Health Insurance (SHI) claims data.

Methods

A retrospective observational study was conducted using data from January 1st, 2015 to December 31st, 2022. Two coding algorithms – one restrictive and one inclusive – were developed to identify primary IgAN cases based on ICD-10-GM codes. The restrictive algorithm identified cases based on histologically confirmed diagnoses, while the inclusive algorithm included a broader range of related diagnoses. Annual incidence and prevalence rates were calculated and extrapolated to the German population.

Results

The mean prevalence rate from 2017–2022 ranged from 4.5 (restrictive codes) to 38.3 (inclusive codes) cases per 100,000 individuals, demonstrating the orphan nature of primary IgAN. Mean incidence rates ranged from 0.2 to 0.6 cases per 100,000 individuals. In 2022, this corresponded to an estimated 4,043 to 32,229 prevalent cases and 164 to 538 incident cases in Germany.

Conclusion

This study presents an approach for estimating disease epidemiology in the absence of specific diagnostic codes, using primary IgAN as an example. While our dual-algorithm method provides valuable insights into the incidence and prevalence of primary IgAN in Germany, it also highlights the need for consistent coding practices and specific diagnostic codes for accurate epidemiological assessments.