Estudo piloto de validação de um chatbot de rastreamento, implementado para direcionar a teleassistência em COVID-19
Resumo
A pandemia do novo coronavírus tem sobrecarregado os sistemas de saúde ao limite da capacidade de atendimento. Nosso objetivo foi avaliar a eficácia de um chatbot desenvolvido para triagem de pacientes, antes de teleconsulta, para identificar sintomas de COVID-19. Sintomas informados no diálogo foram comparados com os relatados aos médicos, em um serviço de urgência. Em 96 pacientes, dispneia foi o sintoma mais frequente (16,6%) e o único que mostrou concordância moderada com a história registrada em prontuário eletrônico (Kappa=0,605). Concluindo, a tecnologia mostrou-se útil para detectar um dos sintomas graves da COVID-19, mas não foi possível evidenciar sua eficácia em relação aos sintomas menores.
Referências
World Health Organization. Coronavirus disease (COVID-19) pandemic. Acessível em: [link]. Data do acesso: 26/03/2021.
JUDSON, Timothy J. et al. Implementation of a digital chatbot to screen health system employees during the COVID-19 pandemic. Journal of the American Medical Informatics Association, v. 27, n. 9, p. 1450-1455, 2020.
Monitoring and evaluating digital health interventions: a practical guide to conducting research and assessment. Geneva: World Health Organization; 2016. Licence: CC BY- NC-SA 3.0 IGO.
Storm-Versloot MN, Ubbink DT, Kappelhof J, et al. Comparison of an informally structured triage system, the emergency severity index, and the Manchester triage system to distinguish patient priority in the emergency department. Acad. Emerg. Med. 2011; 18(8):822-829.
WILLIAMS, Noelle L. et al. Clinical Integration of Digital Solutions in Health Care: An Overview of the Current Landscape of Digital Technologies in Cancer Care. American Society of Clinical Oncology, 2018.
MARTIN,Alistrair et al. An artificial intelligencebased firstline defence against COVID19: digitally screening citizens for risks via a chatbot, 2020.
GABARRON, Elia et al. What do we know about the use of chatbots for public health? European Federation for Medical Informatics, 2020.
MILNES-IVES et al. The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review .Journal of Medical Internet Research,vol. 22, e20346,p.1, 2020.
JUDSON, Timothy J. et al. Implementation of a digital chatbot to screen health system employees during the COVID-19 pandemic. Journal of the American Medical Informatics Association, v. 27, n. 9, p. 1450-1455, 2020.
Monitoring and evaluating digital health interventions: a practical guide to conducting research and assessment. Geneva: World Health Organization; 2016. Licence: CC BY- NC-SA 3.0 IGO.
Storm-Versloot MN, Ubbink DT, Kappelhof J, et al. Comparison of an informally structured triage system, the emergency severity index, and the Manchester triage system to distinguish patient priority in the emergency department. Acad. Emerg. Med. 2011; 18(8):822-829.
WILLIAMS, Noelle L. et al. Clinical Integration of Digital Solutions in Health Care: An Overview of the Current Landscape of Digital Technologies in Cancer Care. American Society of Clinical Oncology, 2018.
MARTIN,Alistrair et al. An artificial intelligencebased firstline defence against COVID19: digitally screening citizens for risks via a chatbot, 2020.
GABARRON, Elia et al. What do we know about the use of chatbots for public health? European Federation for Medical Informatics, 2020.
MILNES-IVES et al. The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review .Journal of Medical Internet Research,vol. 22, e20346,p.1, 2020.
Publicado
15/06/2021
Como Citar
CATEB, Gabriel F.; AMARAL, Samuel; GONÇALVES, Samuel C. L.; OLIVEIRA, Isaias J. R.; PRATES, Raquel O.; CHAGAS, Bruno A.; MARCOLINO, Milena S.; REIS, Zilma S. N..
Estudo piloto de validação de um chatbot de rastreamento, implementado para direcionar a teleassistência em COVID-19. In: CONCURSO DE TRABALHOS DE INICIAÇÃO CIENTÍFICA - SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 21. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 97-102.
ISSN 2763-8987.
DOI: https://doi.org/10.5753/sbcas.2021.16108.
