What question did this study set out to answer?

The study aims to evaluate how diagnosis code distributions in EHR data vary based on different extraction time points.

Temporal Variability in Diagnosis Code Distributions Across Extraction Time Points in a Multicenter Integrated EHR Database: A Snapshot Comparison Study

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Retrospective study evaluates variability in diagnosis codes in EHR data, highlighting extraction timing importance.

The study aims to evaluate how diagnosis code distributions in EHR data vary based on different extraction time points.
Conducted a retrospective, descriptive, observational study using data from a multicenter integrated EHR database in Japan.
Extracted diagnostic data at three time points: October 2023, October 2024, and October 2025.
Quantified changes in diagnosis code distributions using the Jensen–Shannon distance (JSD).
JSD values for ICD-10 distributions were non-zero, indicating variability across extraction time points.
Facility C showed a JSD of 0.0310 in 2024, markedly higher than other facilities.
Acute conditions generally decreased, while chronic conditions increased between extraction time points.

Lee et al. (2026) studied this question.

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