| Title |
A Semantic-Based Model for Triage Patients in Emergency Departments
|
|---|---|
| Published in |
Journal of Medical Systems, March 2017
|
| DOI | 10.1007/s10916-017-0710-y |
| Pubmed ID | |
| Authors |
Guilherme Wunsch, Cristiano A. da Costa, Rodrigo R. Righi |
| Abstract |
Triage is a process performed in an emergency department that aims to sort patients according to their need for care. When performed speedily and correctly, this process can potentially increase the chances of survival for a patient with serious complications. This study aims to develop a computer model, called UbiTriagem, which supports the process of triage using the concepts of web semantics and ubiquitous computing focused on healthcare. For evaluating the proposal, we performed an analysis of scenario-driven triage based on previously determined ratings. In addition, we conducted a usability evaluation in emergency department with the developed prototype with two user groups: nurses and patients. The main scientific contribution is the automatic triage assessment based on the gathering of patient data on mobile devices, performed automatically through the use of a reasoning technique in an ontology. The results for all evaluations were very positive. The automatic triage assessment has been assertive in 93.3% of the cases and, after adjustments in the model, in 100% of the cases. Regarding user satisfaction, we obtained rates of 98.7% and 96% when considering perception of utility and ease of use, respectively. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 51 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 22% |
| Student > Ph. D. Student | 8 | 16% |
| Student > Bachelor | 6 | 12% |
| Researcher | 5 | 10% |
| Professor > Associate Professor | 3 | 6% |
| Other | 8 | 16% |
| Unknown | 10 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 10 | 20% |
| Nursing and Health Professions | 9 | 18% |
| Medicine and Dentistry | 7 | 14% |
| Engineering | 4 | 8% |
| Biochemistry, Genetics and Molecular Biology | 2 | 4% |
| Other | 6 | 12% |
| Unknown | 13 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 April 2018.
All research outputs
#18,603,172
of 23,043,346 outputs
Outputs from Journal of Medical Systems
#821
of 1,161 outputs
Outputs of similar age
#235,101
of 307,949 outputs
Outputs of similar age from Journal of Medical Systems
#18
of 21 outputs
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