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Approaches for the identification of chronic kidney disease in CPRD-HES-linked studies

Sreeram Ramagopalan1, Thomas P Leahy2, Elaine Stamp2

  • 1Centre for Observational Research & Data Sciences, Bristol-Myers Squibb, Uxbridge, UK.

Journal of Comparative Effectiveness Research
|March 10, 2020
PubMed

Insights

Identifying chronic kidney disease (CKD) in CPRD-HES data requires combining test results and diagnostic codes. Relying solely on codes underestimates CKD prevalence, affecting patient care.

Area of Science:

  • Nephrology
  • Epidemiology
  • Health Informatics

Background:

  • Chronic kidney disease (CKD) identification in large healthcare datasets like CPRD-HES is crucial for patient management.
  • Existing methods for CKD detection in CPRD-HES may have limitations.

Purpose of the Study:

  • To compare different methods for identifying CKD stages in patients with nonvalvular atrial fibrillation within the CPRD-HES database.
  • To determine the most accurate approach for CKD prevalence estimation in this population.

Main Methods:

  • Utilized Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics (HES) data.
  • Classified nonvalvular atrial fibrillation patients based on CKD categories using various identification methods.
  • Compared CKD prevalence estimates derived from glomerular filtration rate (GFR)/estimated GFR (eGFR) tests, diagnostic codes, and a combination of both.

Main Results:

  • GFR/eGFR tests alone identified low percentages of CKD stages (e.g., 3.5% stage 2, 2.7% stage 3).
  • Diagnostic codes alone resulted in lower prevalence estimates (e.g., 1.4% stage 3, 0.4% stage 4).
  • Combining test records and diagnostic codes yielded higher prevalence rates (e.g., 3.5% stage 2, 4.0% stage 3, 0.6% stage 4, 0.4% stage 5).

Conclusions:

  • A combined approach using both test records and diagnostic codes is recommended for accurate CKD identification in CPRD-HES.
  • Diagnostic codes alone significantly underestimate the prevalence of CKD.
  • Accurate CKD identification is vital for appropriate clinical management and research.

Keywords:
CPRDGFRatrial fibrillationchronic kidney diseasediagnostic codespharmacoepidemiologytest results

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