Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Research, Society and Development |
Texto Completo: | https://rsdjournal.org/index.php/rsd/article/view/19743 |
Resumo: | This study developed a software that calculates the chance of the health professional having zero, one, two, three or four or more accidents with biological hazards. Data from 111 questionnaires of health workers in primary and emergency care were used. The program achieved 95% accuracy in the training set (n=88) and 74% in the test set (n=23). The statistically significant associations, which also relied on data from 1,094 work accident reports, were greater abandonment of follow-up by physicians after an accident with biological materials in comparison with other professionals (p=0.02), nursing technicians and a higher prevalence of accidents with biological materials than other professionals (p<0.001), emergency care workers have more accidents with biological materials than primary care professionals (p<0.001) and increased follow-up abandonment after an accident with biological materials in the 2016-2018 period compared to 2007-2009 (p<0.001). |
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Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionalsUso de la inteligencia artificial para la predicción de accidentes de trabajo con materiales biológicos en profesionales de la saludUso da inteligência artificial para predição de acidentes de trabalho com materiais biológicos em profissionais da saúdeInteligência ArtificialAcidentes OcupacionaisSaúde do TrabalhadorAtenção primária à saúde.Inteligencia ArtificialAccidentes LaboralesSalud LaboralAtención primaria.Artificial IntelligenceOccupational AccidentsOccupational HealthPrimary health care.This study developed a software that calculates the chance of the health professional having zero, one, two, three or four or more accidents with biological hazards. Data from 111 questionnaires of health workers in primary and emergency care were used. The program achieved 95% accuracy in the training set (n=88) and 74% in the test set (n=23). The statistically significant associations, which also relied on data from 1,094 work accident reports, were greater abandonment of follow-up by physicians after an accident with biological materials in comparison with other professionals (p=0.02), nursing technicians and a higher prevalence of accidents with biological materials than other professionals (p<0.001), emergency care workers have more accidents with biological materials than primary care professionals (p<0.001) and increased follow-up abandonment after an accident with biological materials in the 2016-2018 period compared to 2007-2009 (p<0.001).El objetivo de este estudio es desarrollar un programa informático que calcule la probabilidad de que un profesional de salud tenga cero, uno, dos, tres o cuatro o más accidentes con riesgo biológico. Se utilizaron datos de 111 cuestionarios de trabajadores de la atención primaria y de urgencias. El programa alcanzó 95% de precisión en el conjunto entrenamiento (n=88) y 74% en el conjunto de prueba (n=23). Las asociaciones estadísticamente significativas, que también incluyeron datos de 1.094 Comunicaciones de Accidentes de Trabajo, fueron el mayor abandono del seguimiento por parte de los médicos tras un accidente con materiales biológicos en comparación con otros profesionales (p=0,02), los técnicos de enfermería y mayor prevalencia de accidentes con materiales biológicos que otros profesionales (p<0,001), los trabajadores de urgencias presentan más accidentes con material biológico que los profesionales de atención primaria (p<0,001) y aumento del abandono tras accidente con material biológico en el trienio 2016-2018 respecto a 2007-2009 (p<0,001).Este estudo buscou desenvolver um software que calcula a chance de o profissional de saúde ter zero, um, dois, três ou quatro ou mais acidentes com riscos biológicos. Para tal foram utilizados dados de 111 questionários de trabalhadores da saúde da atenção primária e pronto atendimento. O programa atingiu 95% de acurácia no conjunto de treinamento (n=88) e 74% no conjunto de teste (n=23). As associações estatisticamente significantes, que contaram também com dados de 1.094 Comunicações de Acidente de Trabalho, foram maior abandono do acompanhamento por médicos após acidente com materiais biológicos na comparação com outros profissionais (p=0.02), técnicos em enfermagem e maior prevalência de acidentes com materiais biológicos que outros profissionais (p<0.001), trabalhadores de pronto atendimento apresentam mais acidentes com materiais biológicos que profissionais da atenção primária (p<0.001) e aumento do abandono após acidente com materiais biológicos no triênio 2016-2018 na comparação com 2007-2009 (p<0.001).Research, Society and Development2021-09-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/1974310.33448/rsd-v10i12.19743Research, Society and Development; Vol. 10 No. 12; e93101219743Research, Society and Development; Vol. 10 Núm. 12; e93101219743Research, Society and Development; v. 10 n. 12; e931012197432525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/19743/18007Copyright (c) 2021 Anderson Dillmann Groto; Cássio Marques Perlin; Sonia Mara de Andrade; Mayara Angélica Bolson Salamancahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessGroto, Anderson DillmannPerlin, Cássio Marques Andrade, Sonia Mara de Salamanca, Mayara Angélica Bolson 2021-11-14T20:26:51Zoai:ojs.pkp.sfu.ca:article/19743Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:39:35.144135Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false |
dc.title.none.fl_str_mv |
Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals Uso de la inteligencia artificial para la predicción de accidentes de trabajo con materiales biológicos en profesionales de la salud Uso da inteligência artificial para predição de acidentes de trabalho com materiais biológicos em profissionais da saúde |
title |
Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals |
spellingShingle |
Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals Groto, Anderson Dillmann Inteligência Artificial Acidentes Ocupacionais Saúde do Trabalhador Atenção primária à saúde. Inteligencia Artificial Accidentes Laborales Salud Laboral Atención primaria. Artificial Intelligence Occupational Accidents Occupational Health Primary health care. |
title_short |
Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals |
title_full |
Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals |
title_fullStr |
Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals |
title_full_unstemmed |
Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals |
title_sort |
Use of artificial intelligence for prediction of work accidents with biological risks in healthcare professionals |
author |
Groto, Anderson Dillmann |
author_facet |
Groto, Anderson Dillmann Perlin, Cássio Marques Andrade, Sonia Mara de Salamanca, Mayara Angélica Bolson |
author_role |
author |
author2 |
Perlin, Cássio Marques Andrade, Sonia Mara de Salamanca, Mayara Angélica Bolson |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Groto, Anderson Dillmann Perlin, Cássio Marques Andrade, Sonia Mara de Salamanca, Mayara Angélica Bolson |
dc.subject.por.fl_str_mv |
Inteligência Artificial Acidentes Ocupacionais Saúde do Trabalhador Atenção primária à saúde. Inteligencia Artificial Accidentes Laborales Salud Laboral Atención primaria. Artificial Intelligence Occupational Accidents Occupational Health Primary health care. |
topic |
Inteligência Artificial Acidentes Ocupacionais Saúde do Trabalhador Atenção primária à saúde. Inteligencia Artificial Accidentes Laborales Salud Laboral Atención primaria. Artificial Intelligence Occupational Accidents Occupational Health Primary health care. |
description |
This study developed a software that calculates the chance of the health professional having zero, one, two, three or four or more accidents with biological hazards. Data from 111 questionnaires of health workers in primary and emergency care were used. The program achieved 95% accuracy in the training set (n=88) and 74% in the test set (n=23). The statistically significant associations, which also relied on data from 1,094 work accident reports, were greater abandonment of follow-up by physicians after an accident with biological materials in comparison with other professionals (p=0.02), nursing technicians and a higher prevalence of accidents with biological materials than other professionals (p<0.001), emergency care workers have more accidents with biological materials than primary care professionals (p<0.001) and increased follow-up abandonment after an accident with biological materials in the 2016-2018 period compared to 2007-2009 (p<0.001). |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-09-14 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/19743 10.33448/rsd-v10i12.19743 |
url |
https://rsdjournal.org/index.php/rsd/article/view/19743 |
identifier_str_mv |
10.33448/rsd-v10i12.19743 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/19743/18007 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Research, Society and Development |
publisher.none.fl_str_mv |
Research, Society and Development |
dc.source.none.fl_str_mv |
Research, Society and Development; Vol. 10 No. 12; e93101219743 Research, Society and Development; Vol. 10 Núm. 12; e93101219743 Research, Society and Development; v. 10 n. 12; e93101219743 2525-3409 reponame:Research, Society and Development instname:Universidade Federal de Itajubá (UNIFEI) instacron:UNIFEI |
instname_str |
Universidade Federal de Itajubá (UNIFEI) |
instacron_str |
UNIFEI |
institution |
UNIFEI |
reponame_str |
Research, Society and Development |
collection |
Research, Society and Development |
repository.name.fl_str_mv |
Research, Society and Development - Universidade Federal de Itajubá (UNIFEI) |
repository.mail.fl_str_mv |
rsd.articles@gmail.com |
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1797052808284864512 |