Sepsis risk assessment: a retrospective analysis after a cognitive risk management robot (Robot Laura®) implementation in a clinical-surgical unit
Res. Biomed. Eng. (Online)
; 34(4): 310-316, Oct.-Dec. 2018. tab, graf
Article
in English
| LILACS
| ID: biblio-984969
Responsible library:
BR1.1
ABSTRACT
Abstract Introduction This study aimed at evaluating the impact of the implementation of a cognitive robot (Robot Laura™) on processes related to the identification and care of patients with risk of sepsis in a clinical-surgical unit of a private hospital in Curitiba-PR. Methods The study data were obtained from the retrospective review of medical records of patients identified with infection and/or sepsis, in the period of six months before and after the implementation of such technology in the hospital. In addition, the Average Attendance Time (AAT) was obtained from the autonomous reading of the robot. Results The average time/median until antibiotic prescription from the first identified sign of infection, with or without sepsis, was 390/77 and 109/58 minutes, respectively, in the six months before and after implementation of the technology. However, this difference was not statistically significant (p = 0.85). Regarding AAT, it was possible to observe a reduction from 305 to 280 minutes when comparing the periods of six months before and after the implementation of the technology (p = 0.02). Conclusion Technologies such as this may be promising in helping healthcare professionals to identify risky situations for patients, as well as in assisting them to optimize the care required. However, further studies, with a greater number of subjects and with different scenarios, are necessary to consistently validate the results found.
Full text:
Available
Collection:
International databases
Health context:
Sustainable Health Agenda for the Americas
Health problem:
Goal 3 Human resources for health
Database:
LILACS
Type of study:
Etiology study
/
Risk factors
Language:
English
Journal:
Res. Biomed. Eng. (Online)
Journal subject:
Engenharia Biomdica
Year:
2018
Document type:
Article
Affiliation country:
Brazil
Institution/Affiliation country:
Federal University of Technology - Paraná/BR
/
Laura Company/BR
/
Nossa Senhora das Graças Hospital/BR