ArticleScientific reports2023
The quality of vital signs measurements and value preferences in electronic medical records varies by hospital, specialty, and patient demographics.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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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
8 citing papers in PubMed.
- Impact of a clinical atrial fibrillation risk estimation tool on cardiac rhythm monitor utilization following acute ischemic stroke: A prepost clinical trial.American heart journal · 2025Trial
- Assessment of Electronic Clinical Monitoring Systems in the Pediatric Intensive Care Unit: Prospective Concordance Study.JMIR formative research · 2026Article
- Multimodal data for predictive medicine: algorithmic fusion of clinical data in anesthesiology and intensive care.Frontiers in medicine · 2026Article
- Unraveling the Implications of Digit Bias in Digital Health - A Literature Review.Internal medicine (Tokyo, Japan) · 2025Review
- Article
- The Organization of Vital Signs for Pattern Recognition.Medical science educator · 2025Article
- Building a Foundation for High-Quality Health Data: Multihospital Case Study in Belgium.JMIR medical informatics · 2024Article
- Motif discovery in hospital ward vital signs observation networks.Network modeling and analysis in health informatics and bioinformatics · 2024Article
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Authors and funding
7 authors.
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Abstract
We aimed to assess the frequency of value preferences in recording of vital signs in electronic healthcare records (EHRs) and associated patient and hospital factors. We used EHR data from Oxford University Hospitals, UK, between 01-January-2016 and 30-June-2019 and a maximum likelihood estimator to determine the prevalence of value preferences in measurements of systolic and diastolic blood pressure (SBP/DBP), heart rate (HR) (readings ending in zero), respiratory rate (multiples of 2 or 4), and temperature (readings of 36.0 °C). We used multivariable logistic regression to investigate associations between value preferences and patient age, sex, ethnicity, deprivation, comorbidities, calendar time, hour of day, days into admission, hospital, day of week and speciality. In 4,375,654 records from 135,173 patients, there was an excess of temperature readings of 36.0 °C above that expected from the underlying distribution that affected 11.3% (95% CI 10.6-12.1%) of measurements, i.e. these observations were likely inappropriately recorded as 36.0 °C instead of the true value. SBP, DBP and HR were rounded to the nearest 10 in 2.2% (1.4-2.8%) and 2.0% (1.3-5.1%) and 2.4% (1.7-3.1%) of measurements. RR was also more commonly recorded as multiples of 2. BP digit preference and an excess of temperature recordings of 36.0 °C were more common in older and male patients, as length of stay increased, following a previous normal set of vital signs and typically more common in medical vs. surgical specialities. Differences were seen between hospitals, however, digit preference reduced over calendar time. Vital signs may not always be accurately documented, and this may vary by patient groups and hospital settings. Allowances and adjustments may be needed in delivering care to patients and in observational analyses and predictive tools using these factors as outcomes or exposures.
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