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Sepsis risk assessment: a retrospective analysis after a cognitive risk management robot (Robot Laura®) implementation in a clinical-surgical unit
Kalil, Aline Junskowski; Dias, Viviane Maria de Carvalho Hessel; Rocha, Cristian da Costa; Morales, Hugo Manuel Paz; Fressatto, Jacson Luiz; Faria, Rubens Alexandre de.
  • Kalil, Aline Junskowski; Federal University of Technology - Paraná. Biomedical Engineering Program. Curitiba. BR
  • Dias, Viviane Maria de Carvalho Hessel; Nossa Senhora das Graças Hospital. Infection Control Department. Curitiba. BR
  • Rocha, Cristian da Costa; Laura Company. Curitiba. BR
  • Morales, Hugo Manuel Paz; Laura Company. Curitiba. BR
  • Fressatto, Jacson Luiz; Laura Company. Curitiba. BR
  • Faria, Rubens Alexandre de; Federal University of Technology - Paraná. Biomedical Engineering Program. Curitiba. BR
Res. Biomed. Eng. (Online) ; 34(4): 310-316, Oct.-Dec. 2018. tab, graf
Artigo em Inglês | LILACS | ID: biblio-984969
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.


Texto completo: DisponíveL Índice: LILACS (Américas) Tipo de estudo: Estudo de etiologia / Fatores de risco Idioma: Inglês Revista: Res. Biomed. Eng. (Online) Assunto da revista: Engenharia Biom‚dica Ano de publicação: 2018 Tipo de documento: Artigo País de afiliação: Brasil Instituição/País de afiliação: Federal University of Technology - Paraná/BR / Laura Company/BR / Nossa Senhora das Graças Hospital/BR

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Texto completo: DisponíveL Índice: LILACS (Américas) Tipo de estudo: Estudo de etiologia / Fatores de risco Idioma: Inglês Revista: Res. Biomed. Eng. (Online) Assunto da revista: Engenharia Biom‚dica Ano de publicação: 2018 Tipo de documento: Artigo País de afiliação: Brasil Instituição/País de afiliação: Federal University of Technology - Paraná/BR / Laura Company/BR / Nossa Senhora das Graças Hospital/BR