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Beyond the numbers: the importance of contextual data when reusing blood pressure data from electronic health records

  • Marieke E. Grünewald
  • , Erik Koomen
  • , Lex M. van Loon
  • , Ankit Gupta
  • , Robin W.M. Vernooij
  • , Wouter W. van Solinge
  • , Teus Kappen
  • , Saskia Haitjema*
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

With the digitization of health records, the reuse of Electronic Health Record (EHR) data has become increasingly prevalent in research. Using blood pressure as a case study, this paper examines the complexities and practical realities of reusing EHR data, emphasizing the importance of contextual information for accurate interpretation. Although blood pressure data derived from EHR systems may appear straightforward—often captured by machines or derived from standardized workflows—their reuse is frequently complicated by variability in measurement methods and clinical contexts, which can produce seemingly similar but clinically distinct blood pressure readings. The paper begins with the physiology of blood pressure and the various techniques used to measure it. This is followed by an analysis of different clinical settings—i.e., the different pathophysiological situations—that may affect both measurement practices and data interpretation. The paper then explores how these measurements are recorded in EHR systems and concludes with practical guidance to support researchers in identifying blood pressure data that are truly fit for the intended research purpose. By acknowledging the inherent complexities of healthcare data and making informed data selection decisions, researchers can better harness the potential of EHRs to generate meaningful insights that ultimately improve patient care.

Original languageEnglish
Article number1664213
JournalFrontiers in Digital Health
Volume7
Early online date3 Sept 2025
DOIs
Publication statusPublished - 2025

Keywords

  • blood pressure
  • contextual data
  • data reuse
  • EHDS
  • electronic health records
  • fit for purpose
  • semantic interoperability

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