Beyond the numbers: the importance of contextual data when reusing blood pressure data from Electronic Health Records

Marieke E. Grünewald¹Erik Koomen²Lex M. van Loon^3,4Ankit Gupta⁵Robin W.M. Vernooij^1,6Wouter W. van Solinge¹Teus Kappen^7,8Saskia Haitjema^1*

• ¹Central Diagnostic Laboratory, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
• ²Pediatric Intensive Care Unit, Wilhelmina’s Children’s Hospital, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
• ³Intensive Care Center, University Medical Center Utrecht, Utrecht, Netherlands
• ⁴Cardiovascular and Respiratory Physiology, Technical Medical Centre, University of Twente, Enschede, Netherlands
• ⁵Siemens Healthcare Private Limited, Bangalore, India
• ⁶Department of Nephrology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
• ⁷Department of Anesthesiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
• ⁸Directorate Information Technology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands

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.