ArticleFrontiers in digital health2025
Beyond the numbers: the importance of contextual data when reusing blood pressure data from electronic health records.
Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Extracting Signs and Symptoms of Hypertensive Disorders in Pregnancy from Clinical Notes Using Natural Language Processing.Maternal and child health journal · 2026Observational
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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