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Assessing Plausibility of Clinical Fact Dates in Real World Data
Matthias Hüser1, Lydia González1, Matvey B Palchuk1
1TriNetX, LLC, Cambridge, Massachusetts, USA.
Abstract:
We present a simple quantitative framework to assess timestamp plausibility in real world clinical data using the Jensen-Shannon divergence. Applied to encounter start dates across the TriNetX US network, the method identified healthcare organizations with abnormal patterns caused by binning or clustering of dates. This approach has the potential to enable systematic detection of anomalies and supports continuous data quality improvement in federated healthcare data sets.
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