An algorithm for identifying visits due to pediatric lower acute respiratory infections in electronic clinical records

Background: Due to ambiguities in terminology, acute lower respiratory infections (ALRI) in childhood are frequently not properly recorded, especially during outpatient visits. A tool that accurately identifies them, would assess the impact on respiratory health of massive harms, and design policies...

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Autores principales: González Pannia, Paula, Rodriguez Tablado , Manuel, Esteban, Santiago, Abrutzky, Rosana, Torres, Fernando Adrian, Dominguez, Paula, Ossorio, Fabiana, Ferrero, Fernando
Formato: Artículo revista
Lenguaje:Español
Publicado: Universidad Nacional Córdoba. Facultad de Ciencias Médicas. Secretaria de Ciencia y Tecnología 2021
Materias:
electronic health records
child
Respiratory Tract Infections
registros electrónicos de salud
niño
Infecciones del Sistema Respiratorio
registros eletrônicos de saúde
crianças
Infecções Respiratórias
Acceso en línea:https://revistas.unc.edu.ar/index.php/med/article/view/30162
Aporte de:
Revista de la Facultad de Ciencias Médicas de Córdoba de Universidad Nacional de Córdoba
id I10-R327-article-30162
record_format ojs
institution Universidad Nacional de Córdoba
institution_str I-10
repository_str R-327
container_title_str Revista de la Facultad de Ciencias Médicas de Córdoba
language Español
format Artículo revista
topic electronic health records
child
Respiratory Tract Infections
registros electrónicos de salud
niño
Infecciones del Sistema Respiratorio
registros eletrônicos de saúde
crianças
Infecções Respiratórias
spellingShingle electronic health records
child
Respiratory Tract Infections
registros electrónicos de salud
niño
Infecciones del Sistema Respiratorio
registros eletrônicos de saúde
crianças
Infecções Respiratórias
González Pannia, Paula
Rodriguez Tablado , Manuel
Esteban, Santiago
Abrutzky, Rosana
Torres, Fernando Adrian
Dominguez, Paula
Ossorio, Fabiana
Ferrero, Fernando
An algorithm for identifying visits due to pediatric lower acute respiratory infections in electronic clinical records
topic_facet electronic health records
child
Respiratory Tract Infections
registros electrónicos de salud
niño
Infecciones del Sistema Respiratorio
registros eletrônicos de saúde
crianças
Infecções Respiratórias
author González Pannia, Paula
Rodriguez Tablado , Manuel
Esteban, Santiago
Abrutzky, Rosana
Torres, Fernando Adrian
Dominguez, Paula
Ossorio, Fabiana
Ferrero, Fernando
author_facet González Pannia, Paula
Rodriguez Tablado , Manuel
Esteban, Santiago
Abrutzky, Rosana
Torres, Fernando Adrian
Dominguez, Paula
Ossorio, Fabiana
Ferrero, Fernando
author_sort González Pannia, Paula
title An algorithm for identifying visits due to pediatric lower acute respiratory infections in electronic clinical records
title_short An algorithm for identifying visits due to pediatric lower acute respiratory infections in electronic clinical records
title_full An algorithm for identifying visits due to pediatric lower acute respiratory infections in electronic clinical records
title_fullStr An algorithm for identifying visits due to pediatric lower acute respiratory infections in electronic clinical records
title_full_unstemmed An algorithm for identifying visits due to pediatric lower acute respiratory infections in electronic clinical records
title_sort algorithm for identifying visits due to pediatric lower acute respiratory infections in electronic clinical records
description Background: Due to ambiguities in terminology, acute lower respiratory infections (ALRI) in childhood are frequently not properly recorded, especially during outpatient visits. A tool that accurately identifies them, would assess the impact on respiratory health of massive harms, and design policies to prevent or mitigate their effects. We aimed to design an algorithm that allows identifying children with ALRI based on data from the electronic clinical record (ECR) of the Government of the City of Buenos Aires (GCBA). Methodos: From the ECR-GCBA database, we randomly selected 1000 outpatient visits of patients aged under 2 years. Terms showing that the visit was due to LARI were searched using an algorithm based on hard rules. Another dataset including 800 visits was used to adjust the algorithm and, finally, its performance was tested in a third dataset of 800 queries corresponding to the entire year 2018. Results: In the validation set, our tool identified LARI with sensitivity 88.24%, specificity 97.5%, PPV 86.07% and NPV 97.93%. Conclusion: Our search algorithm allows us to identify with acceptable precision the outpatient visits related to LARI in children under 2 years of age from electronic clinical records.
publisher Universidad Nacional Córdoba. Facultad de Ciencias Médicas. Secretaria de Ciencia y Tecnología
publishDate 2021
url https://revistas.unc.edu.ar/index.php/med/article/view/30162
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last_indexed 2024-09-03T21:02:04Z
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spelling I10-R327-article-301622021-11-18T12:43:09Z An algorithm for identifying visits due to pediatric lower acute respiratory infections in electronic clinical records Algoritmo para identificación de consultas por infección respiratoria aguda baja en pediatría en registros clínicos electrónicos Algoritmo para identificar infecções respiratórias agudas inferiores em consultas médicas por meio de prontuários eletrônicos González Pannia, Paula Rodriguez Tablado , Manuel Esteban, Santiago Abrutzky, Rosana Torres, Fernando Adrian Dominguez, Paula Ossorio, Fabiana Ferrero, Fernando electronic health records child Respiratory Tract Infections registros electrónicos de salud niño Infecciones del Sistema Respiratorio registros eletrônicos de saúde crianças Infecções Respiratórias Background: Due to ambiguities in terminology, acute lower respiratory infections (ALRI) in childhood are frequently not properly recorded, especially during outpatient visits. A tool that accurately identifies them, would assess the impact on respiratory health of massive harms, and design policies to prevent or mitigate their effects. We aimed to design an algorithm that allows identifying children with ALRI based on data from the electronic clinical record (ECR) of the Government of the City of Buenos Aires (GCBA). Methodos: From the ECR-GCBA database, we randomly selected 1000 outpatient visits of patients aged under 2 years. Terms showing that the visit was due to LARI were searched using an algorithm based on hard rules. Another dataset including 800 visits was used to adjust the algorithm and, finally, its performance was tested in a third dataset of 800 queries corresponding to the entire year 2018. Results: In the validation set, our tool identified LARI with sensitivity 88.24%, specificity 97.5%, PPV 86.07% and NPV 97.93%. Conclusion: Our search algorithm allows us to identify with acceptable precision the outpatient visits related to LARI in children under 2 years of age from electronic clinical records. Introducción: Debido a ambigüedades en la nomenclatura, las infecciones respiratorias agudas bajas (IRAB) en la infancia frecuentemente no son debidamente registradas, especialmente durante las consultas ambulatorias. Contar con una herramienta que las identifique con precisión, permitirá evaluar el impacto en la salud respiratoria de noxas de alcance masivo y diseñar las políticas para prevenirlas o mitigar sus efectos. Nuestro objetivo fue construir un algoritmo que permita identificar niños con IRAB a partir de los datos de la historia clínica electrónica (HCE) del Gobierno de la Ciudad de Buenos Aires (GCBA). Métodos: Utilizando la HCE-GCBA, se seleccionaron aleatoriamente 1000 consultas ambulatorias de pacientes menores de 2 años. Se buscaron términos que hicieran referencia a que la consulta era motivada por IRAB, con los que se desarrolló un algoritmo basado en reglas duras. Se utilizó otro set de datos de 800 consultas para ajustar el algoritmo y, finalmente, se validó su desempeño en un tercer set de 800 consultas correspondientes a todo el año 2018. Resultados: En el set de validación, la herramienta desarrollada identificó IRAB con sensibilidad 88,24%, especificidad 97,5%, VPP 86,07% y VPN 97,93%. Conclusión: El algoritmo de búsqueda desarrollado permite identificar con aceptable precisión las consultas ambulatorias relacionadas con IRAB en niños menores de 2 años. INTRODUÇÃO: Devido à diferença de nomenclatura, as infecções respiratórias agudas inferiores não são registradas duante a  infância, principalmente nas consultas ambulatoriais. Uma ferramenta que as identifica com precisão, permitirá avaliar impacto na saúde respiratória de grande alcance e projetar as politicas para prevenir ou mitigar os efeitos. Nosso objetivo é construir um algoritmo que faça possível a identificação de crianças com infecções respiratórias inferiores por meio dos dados do prontuário eletrônico do Governo da Cidade de Buenos Aires. Métodos: Usando a ferramenta mencionada, será selecionado em aliatoria 1000 consultas ambulatoriais do pacientes menos de 2 anos de idade.  Serão procurados termos que se referem à consulta gerada por infecções respiratórias inferiore, para isso um algoritmo baseado em regras rígidas foi desenvolvido. Então, o algoritmo foi ajustado usando outro conjunto do 800 consultas. E, finalmente, seu desempenho foi validado por um terceiro conjunto de 800 consultas em 2018. Resultados: No conjunto de validação, a ferramenta desenvolvida detectou infecções com sensibilidade 88.24%, especificidade 97,5%, VPP 86,07% e VPN 97,93%. Conclusão O algoritmo desenvolvido torna possivel identificar com precisão as consultas ambulatoriais do infecções respiratórias agudas inferiores no crianças menores do 2 anos de idade. Universidad Nacional Córdoba. Facultad de Ciencias Médicas. Secretaria de Ciencia y Tecnología 2021-09-06 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf text/html https://revistas.unc.edu.ar/index.php/med/article/view/30162 10.31053/1853.0605.v78.n3.30162 Revista de la Facultad de Ciencias Médicas de Córdoba.; Vol. 78 No. 3 (2021); 283-286 Revista de la Facultad de Ciencias Médicas de Córdoba; Vol. 78 Núm. 3 (2021); 283-286 Revista da Faculdade de Ciências Médicas de Córdoba; v. 78 n. 3 (2021); 283-286 1853-0605 0014-6722 10.31053/1853.0605.v78.n3 spa https://revistas.unc.edu.ar/index.php/med/article/view/30162/35155 https://revistas.unc.edu.ar/index.php/med/article/view/30162/35281 Derechos de autor 2021 Universidad Nacional de Córdoba http://creativecommons.org/licenses/by-nc/4.0

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