Observational studyBMC emergency medicine2018
Man vs machine in emergency medicine - a study on the effects of manual and automatic vital sign documentation on data quality and perceived workload, using observational paired sample data and questionnaires.
Observational study in BMC emergency medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Digital Health Data Quality Issues: Systematic Review.Journal of medical Internet research · 2023Pooled it
- Machine learning models powered by emergency medical services data enhance stroke triage in prehospital settings.Scientific reports · 2026Article
- Data completeness and quality of emergency triage in Ethiopian public tertiary hospitals: A multicenter study.African journal of emergency medicine : Revue africaine de la medecine d'urgence · 2025Article
- Artificial intelligence in prehospital emergency care systems in low- and middle-income countries: cure or curiosity? Insights from a qualitative study.Frontiers in public health · 2025Article
- The relationship between electronic health records user interface features and data quality of patient clinical information: an integrative review.Journal of the American Medical Informatics Association : JAMIA · 2023Review
- Design and Implementation of an Informatics Infrastructure for Standardized Data Acquisition, Transfer, Storage, and Export in Psychiatric Clinical Routine: Feasibility Study.JMIR mental health · 2021Article
- Clinical Decision Support and Implications for the Clinician Burnout Crisis.Yearbook of medical informatics · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEmergency medicine is characterized by a high patient flow where timely decisions are essential. Clinical decision support systems have the potential to assist in such decisions but will be dependent on the data quality in electronic health records which often is inadequate. This study explores the effect of automated documentation of vital signs on data quality and workload.
methodsAn observational study of 200 vital sign measurements was performed to evaluate the effects of manual vs automatic documentation on data quality. Data collection using questionnaires was performed to compare the workload on wards using manual or automatic documentation.
resultsIn the automated documentation time to documentation was reduced by 6.1 min (0.6 min vs 7.7 min, p < 0.05) and completeness increased (98% vs 95%, p < 0.05). Regarding workflow temporal demands were lower in the automatic documentation workflow compared to the manual group (50 vs 23, p < 0.05). The same was true for frustration level (64 vs 33, p < 0.05). The experienced reduction in temporal demands was in line with the anticipated, whereas the experienced reduction in frustration was lower than the anticipated (27 vs 54, p < 0.05). DISCUSSION: The study shows that automatic documentation will improve the currency and the completeness of vital sign data in the Electronic Health Record while reducing workload regarding temporal demands and experienced frustration. The study also shows that these findings are in line with staff anticipations but indicates that the anticipations on the reduction of frustration may be exaggerated among the staff. The open-ended answers indicate that frustration focus will change from double documentation of vital signs to technical aspects of the automatic documentation system.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.