ReviewUnfallchirurgie (Heidelberg, Germany)2023
[Application of artificial intelligence systems in the emergency room : Do the communication patterns give indications for possible starting points? An observational study].
Review in Unfallchirurgie (Heidelberg, Germany), 2023. 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
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
1 citing paper in PubMed, 3 citations in OpenAlex.
- The role of big data management, data registries, and machine learning algorithms for optimizing safe definitive surgery in trauma: a review.Patient safety in surgery · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHigh expectations are currently attached to the application of artificial intelligence (AI) in the resuscitation room treatment of trauma patients with respect to the development of decision support systems. No data are available regarding possible starting points for AI-controlled interventions in resuscitation room treatment.
objectiveDo information request behavior and quality of communication indicate possible starting points for AI applications in the emergency room? MATERIAL AND
methodsA 2‑stage qualitative observational study: 1. Development of an observation sheet based on expert interviews that depicts the following six relevant topics: situational factors (course of accident, environment), vital parameters, treatment-specific Information (treatment carried out). trauma-specific factors (injury patterns), medication, special features of the patient (anamnesis, etc.) 2. Observational study Which topics were inquired about during emergency room treatment? Was the exchange of information complete?
resultsThere were 40 consecutive observations in the emergency room. A total of 130 questions: 57/130 inquiries about medication/treatment-specific Information and vital parameters, 19/28 of which were inquiries about medication. Questions about injury-related parameters 31/130 with 18/31 regarding injury patterns, course of accident (8/31) and type of accident (5/31). Questions about medical or demographic background 42/130. Within this group, pre-existing illnesses (14/42) and demographic background (10/42) were the most frequently asked questions. Incomplete exchange of information was found in all six subject areas.
conclusionQuestioning behavior and incomplete communication indicate a cognitive overload. Assistance systems that prevent cognitive overload can maintain decision-making abilities and communication skills. Which AI methods can be used requires further research.
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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.