Trial reportBMC emergency medicine2022
Usability of novel major TraumaApp for digital data collection.
Trial report in BMC emergency medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
2 citing papers in PubMed, 8 citations in OpenAlex.
- Usability assessments in clinical decision support systems.Northern clinics of Istanbul · 2025Article
- Implementation of major trauma app: usability and data completeness.BMC emergency medicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDelivery of major trauma care is complex and often fast paced. Clear and comprehensive documentation is paramount to support effective communication during complex clinical care episodes, and to allow collection of data for audit, research and continuous improvement. Clinical events are typically recorded on paper-based records that are developed for individual centres or systems. As one of the priorities laid out by the Scottish Trauma Network project was to develop an electronic data collection system, the TraumaApp was created as a data collection tool for major trauma that could be adopted worldwide.
methodsThe study was performed as a service evaluation based at the Queen Elizabeth University Hospital Emergency Department. Fifty staff members were recruited in pairs and listened to five paired major trauma standby and handover recordings. Participants were randomised to input data to the TraumaApp and one into the existing paper proforma. The time taken to input data add into was measured, along with time for clarifications and any errors made. Those using the app completed a System Usability Score.
resultsNo statistically significant difference was demonstrated between times taken for data entry for the digital and paper documentation, apart from the Case 5 Handover (p < 0.05). Case 1 showed a significantly higher time for clarifications and number of errors with digital data collection (p = 0.01 and p = 1.79E-05 respectively). There were no other differences between data for the app and the proforma. The mean System Usability score for this cohort was 75 out of 100, with a standard deviation of 17 (rounded to nearest integer).
conclusionDigital real-time recording of clinical events using a tool such as the TraumaApp is comparable to completion of paper proforma. The System Usability Score for the TraumaApp was above the internationally validated standard of acceptable usability. There was no evidence of improvement in use over time or familiarity, most likely due to the brevity of the assessments and the refined user interface. This would benefit from further research, exploring data completeness and a potential mixed methods approach to explore training requirements for use of the TraumaApp.
Indexed as
Identifiers
What OpenQuestion holds
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.