Um modelo ubíquo para retriagem de pacientes baseado na Internet das coisas
Resumo
Triagem é um processo que visa ordenar os pacientes de acordo com sua necessidade de cuidados em emergências de hospitais. Contida nesse processo existe a retriagem, que ocorre quando uma outra avaliação é efetuada caso haja necessidades clínicas para isso ou em um período fixo e recorrente definido pelo protocolo do triagem. Esse trabalho se propôs a desenvolver um modelo computacional que visa utilizar conceitos de computação móvel e ubíqua focados nos cuidados de saúde durante a etapa de retriagem de pacientes. A principal contribuição científica desse trabalho foi inferir o momento correto para efetuar a retriagem através da coleta de sinais vitais dos pacientes fazendo o uso da Internet das coisas. Para a avaliação do modelo proposto foi desenvolvido um protótipo buscando analisar sua aplicação em um cenário criado. Sendo assim, nós concluímos que o modelo desenvolvido é viável para uso nas emergências de hospitais.
Referências
Atzori, L., Iera, A., and Morabito, G. (2010). The internet of things: A survey. Computer networks, 54(15):2787–2805.
Blake, M. B. (2015). An internet of things for healthcare. IEEE Internet Computing, (4):4–6.
Borodin, A., Zavyalova, Y., Zaharov, A., and Yamushev, I. (2015). Architectural approach to the multisource health monitoring application design. In Open Innovations Association (FRUCT), 2015 17TH Conference of, pages 16–21. IEEE.
Christ, M., Grossmann, F., Winter, D., Bingisser, R., and Platz, E. (2010). Modern triage in the emergency department. Deutsches A¨rzteblatt international, 107(50):892.
da Rocha, C. C. L., da Costa, C. A., and da Rosa Righi, R. (2015). Um modelo para monitoramento de sinais vitais do coração baseado em ciência da situação e computação ubíqua. In VII Simpósio Brasileiro de Computação Ubíqua e Pervasiva.
Gelogo, Y. E. and Kim, H.-K. (2013). Unified ubiquitous healthcare system architecture with collaborative model. International Journal of Multimedia and Ubiquitous Engineering, 8(3).
Hassanalieragh, M., Page, A., Soyata, T., Sharma, G., Aktas, M., Mateos, G., Kantarci, B., and Andreescu, S. (2015). Health monitoring and management using internet-ofthings (iot) sensing with cloud-based processing: Opportunities and challenges. In Services Computing (SCC), 2015 IEEE International Conference on, pages 285–292. IEEE.
Jara, A. J., Zamora, M. A., and Skarmeta, A. F. (2012). Knowledge acquisition and management architecture for mobile and personal health environments based on the internet of things. In Trust, Security and Privacy in Computing and Communications (TrustCom), 2012 IEEE 11th International Conference on, pages 1811–1818. IEEE.
Jentsch, M., Ramirez, L., Wood, L., and Elmasllari, E. (2013). The reconfiguration of triage by introduction of technology. In Proceedings of the 15th international conference on Human-computer interaction with mobile devices and services, pages 55–64. ACM.
Jobé, J., Ghuysen, A., G´erard, P., Hartstein, G., and D’Orio, V. (2014). Reliability and validity of a new french-language triage algorithm: the elisa scale. Emergency Medicine Journal, 31(2):115–120.
Krafzig, D., Banke, K., and Slama, D. (2005). Enterprise SOA: service-oriented architecture best practices. Prentice Hall Professional.
Mackway-Jones, K., Marsden, J., and Windle, J. (2014). Emergency triage. Blackwell Publishing, 3 edition.
Marilza Pernas, A., Diaz, A., Motz, R., and Palazzo Moreira de Oliveira, J. (2012). Enriching adaptation in e-learning systems through a situation-aware ontology network. Interactive Technology and Smart Education, 9(2):60–73.
Rahmat, M. H., Annamalai, M., Halim, S. A., and Ahmad, R. (2013). Agent-based modelling and simulation of emergency department re-triage. In Business Engineering and Industrial Applications Colloquium (BEIAC), 2013 IEEE, pages 219–224. IEEE.
Satyanarayanan, M. (2011). Mobile computing: the next decade. ACM SIGMOBILE Mobile Computing and Communications Review, 15(2):2–10.
Schilit, B., Adams, N., and Want, R. (1994). Context-aware computing applications. In First Workshop on Mobile Computing Systems and Applications, 1994. WMCSA 1994, pages 85–90. IEEE.
Weiser, M. (1991). The computer for the 21st century. Scientific american, 265(3):94–104.
Westergren, H., Ferm, M., and H¨aggstr¨om, P. (2014). First evaluation of the paediatric version of the swedish rapid emergency triage and treatment system shows good reliability. Acta Paediatrica, 103(3):305–308.
Worster, A., Sardo, A., Eva, K., Fernandes, C., and Upadhye, S. (2007). Triage tool inter-rater reliability: a comparison of live versus paper case scenarios. Journal of emergency nursing, 33(4):319–323.
Blake, M. B. (2015). An internet of things for healthcare. IEEE Internet Computing, (4):4–6.
Borodin, A., Zavyalova, Y., Zaharov, A., and Yamushev, I. (2015). Architectural approach to the multisource health monitoring application design. In Open Innovations Association (FRUCT), 2015 17TH Conference of, pages 16–21. IEEE.
Christ, M., Grossmann, F., Winter, D., Bingisser, R., and Platz, E. (2010). Modern triage in the emergency department. Deutsches A¨rzteblatt international, 107(50):892.
da Rocha, C. C. L., da Costa, C. A., and da Rosa Righi, R. (2015). Um modelo para monitoramento de sinais vitais do coração baseado em ciência da situação e computação ubíqua. In VII Simpósio Brasileiro de Computação Ubíqua e Pervasiva.
Gelogo, Y. E. and Kim, H.-K. (2013). Unified ubiquitous healthcare system architecture with collaborative model. International Journal of Multimedia and Ubiquitous Engineering, 8(3).
Hassanalieragh, M., Page, A., Soyata, T., Sharma, G., Aktas, M., Mateos, G., Kantarci, B., and Andreescu, S. (2015). Health monitoring and management using internet-ofthings (iot) sensing with cloud-based processing: Opportunities and challenges. In Services Computing (SCC), 2015 IEEE International Conference on, pages 285–292. IEEE.
Jara, A. J., Zamora, M. A., and Skarmeta, A. F. (2012). Knowledge acquisition and management architecture for mobile and personal health environments based on the internet of things. In Trust, Security and Privacy in Computing and Communications (TrustCom), 2012 IEEE 11th International Conference on, pages 1811–1818. IEEE.
Jentsch, M., Ramirez, L., Wood, L., and Elmasllari, E. (2013). The reconfiguration of triage by introduction of technology. In Proceedings of the 15th international conference on Human-computer interaction with mobile devices and services, pages 55–64. ACM.
Jobé, J., Ghuysen, A., G´erard, P., Hartstein, G., and D’Orio, V. (2014). Reliability and validity of a new french-language triage algorithm: the elisa scale. Emergency Medicine Journal, 31(2):115–120.
Krafzig, D., Banke, K., and Slama, D. (2005). Enterprise SOA: service-oriented architecture best practices. Prentice Hall Professional.
Mackway-Jones, K., Marsden, J., and Windle, J. (2014). Emergency triage. Blackwell Publishing, 3 edition.
Marilza Pernas, A., Diaz, A., Motz, R., and Palazzo Moreira de Oliveira, J. (2012). Enriching adaptation in e-learning systems through a situation-aware ontology network. Interactive Technology and Smart Education, 9(2):60–73.
Rahmat, M. H., Annamalai, M., Halim, S. A., and Ahmad, R. (2013). Agent-based modelling and simulation of emergency department re-triage. In Business Engineering and Industrial Applications Colloquium (BEIAC), 2013 IEEE, pages 219–224. IEEE.
Satyanarayanan, M. (2011). Mobile computing: the next decade. ACM SIGMOBILE Mobile Computing and Communications Review, 15(2):2–10.
Schilit, B., Adams, N., and Want, R. (1994). Context-aware computing applications. In First Workshop on Mobile Computing Systems and Applications, 1994. WMCSA 1994, pages 85–90. IEEE.
Weiser, M. (1991). The computer for the 21st century. Scientific american, 265(3):94–104.
Westergren, H., Ferm, M., and H¨aggstr¨om, P. (2014). First evaluation of the paediatric version of the swedish rapid emergency triage and treatment system shows good reliability. Acta Paediatrica, 103(3):305–308.
Worster, A., Sardo, A., Eva, K., Fernandes, C., and Upadhye, S. (2007). Triage tool inter-rater reliability: a comparison of live versus paper case scenarios. Journal of emergency nursing, 33(4):319–323.
Publicado
04/07/2016
Como Citar
WUNSCH, Guilherme; DA COSTA, Cristiano André; RIGHI, Rodrigo da Rosa.
Um modelo ubíquo para retriagem de pacientes baseado na Internet das coisas. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO UBÍQUA E PERVASIVA (SBCUP), 8. , 2016, Porto Alegre.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2016
.
p. 1176-1185.
ISSN 2595-6183.
DOI: https://doi.org/10.5753/sbcup.2016.9466.
