Sectorizing Health Conditions in Quito-Ecuador: A Case Study

Miguel Ortiz; Jhonny Pincay

doi:10.1007/978-3-031-69228-4_32

Sectorizing Health Conditions in Quito-Ecuador: A Case Study

Miguel Ortiz, Jhonny Pincay^*

^*Autor correspondiente de este trabajo

Facultad de Ingeniería

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

Resumen

This manuscript details the conceptualization and implementation of a case study that uses operational data of a clinical laboratory to geographically sectorize health conditions in the city of Quito, Ecuador. Through the application of clustering and association rules discovering, it was possible to identify some of the ailments possibly affecting the population of Quito in different sectors of the city. After the evaluation of the results, it was concluded that although they are not enough to generalize, they provide indications about the main health issues that the population suffers from and that they might be related to the districts’ socioeconomic status. Moreover, such outcomes were considered insightful by three health experts, who manifested that they could be used as starting points for targeted health campaigns for instance.

Idioma original	Inglés
Título de la publicación alojada	Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2023) - Advances in Computer Sciences - Exploring Innovations at the Intersection of Computing Technologies
Editores	Marcelo V. Garcia, Carlos Gordón-Gallegos, Asier Salazar-Ramírez, Carlos Nuñez
Editorial	Springer Science and Business Media Deutschland GmbH
Páginas	481-497
Número de páginas	17
ISBN (versión impresa)	9783031692277
DOI	https://doi.org/10.1007/978-3-031-69228-4_32
Estado	Publicada - 2024
Evento	International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2023 - Ambato, Ecuador Duración: 6 nov. 2023 → 10 nov. 2023

Serie de la publicación

Nombre	Lecture Notes in Networks and Systems
Volumen	775 LNNS
ISSN (versión impresa)	2367-3370
ISSN (versión digital)	2367-3389

Conferencia

Conferencia	International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2023
País/Territorio	Ecuador
Ciudad	Ambato
Período	6/11/23 → 10/11/23

Nota bibliográfica

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Acceder al documento

10.1007/978-3-031-69228-4_32

Otros archivos y enlaces

Enlace a la publicación en Scopus

Citar esto

Ortiz, M., & Pincay, J. (2024). Sectorizing Health Conditions in Quito-Ecuador: A Case Study. En M. V. Garcia, C. Gordón-Gallegos, A. Salazar-Ramírez, & C. Nuñez (Eds.), Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2023) - Advances in Computer Sciences - Exploring Innovations at the Intersection of Computing Technologies (pp. 481-497). (Lecture Notes in Networks and Systems; Vol. 775 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-69228-4_32

Ortiz, Miguel ; Pincay, Jhonny. / Sectorizing Health Conditions in Quito-Ecuador : A Case Study. Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2023) - Advances in Computer Sciences - Exploring Innovations at the Intersection of Computing Technologies. editor / Marcelo V. Garcia ; Carlos Gordón-Gallegos ; Asier Salazar-Ramírez ; Carlos Nuñez. Springer Science and Business Media Deutschland GmbH, 2024. pp. 481-497 (Lecture Notes in Networks and Systems).

@inproceedings{451d8300aa2b485185cec5ba4d088e0e,

title = "Sectorizing Health Conditions in Quito-Ecuador: A Case Study",

abstract = "This manuscript details the conceptualization and implementation of a case study that uses operational data of a clinical laboratory to geographically sectorize health conditions in the city of Quito, Ecuador. Through the application of clustering and association rules discovering, it was possible to identify some of the ailments possibly affecting the population of Quito in different sectors of the city. After the evaluation of the results, it was concluded that although they are not enough to generalize, they provide indications about the main health issues that the population suffers from and that they might be related to the districts{\textquoteright} socioeconomic status. Moreover, such outcomes were considered insightful by three health experts, who manifested that they could be used as starting points for targeted health campaigns for instance.",

keywords = "Association Discovery, Clinical Data, Clustering",

author = "Miguel Ortiz and Jhonny Pincay",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2023 ; Conference date: 06-11-2023 Through 10-11-2023",

year = "2024",

doi = "10.1007/978-3-031-69228-4_32",

language = "English",

isbn = "9783031692277",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "481--497",

editor = "Garcia, {Marcelo V.} and Carlos Gord{\'o}n-Gallegos and Asier Salazar-Ram{\'i}rez and Carlos Nu{\~n}ez",

booktitle = "Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2023) - Advances in Computer Sciences - Exploring Innovations at the Intersection of Computing Technologies",

}

Ortiz, M & Pincay, J 2024, Sectorizing Health Conditions in Quito-Ecuador: A Case Study. En MV Garcia, C Gordón-Gallegos, A Salazar-Ramírez & C Nuñez (eds.), Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2023) - Advances in Computer Sciences - Exploring Innovations at the Intersection of Computing Technologies. Lecture Notes in Networks and Systems, vol. 775 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 481-497, International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2023, Ambato, Ecuador, 6/11/23. https://doi.org/10.1007/978-3-031-69228-4_32

Sectorizing Health Conditions in Quito-Ecuador: A Case Study. / Ortiz, Miguel; Pincay, Jhonny.
Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2023) - Advances in Computer Sciences - Exploring Innovations at the Intersection of Computing Technologies. ed. / Marcelo V. Garcia; Carlos Gordón-Gallegos; Asier Salazar-Ramírez; Carlos Nuñez. Springer Science and Business Media Deutschland GmbH, 2024. p. 481-497 (Lecture Notes in Networks and Systems; Vol. 775 LNNS).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

TY - GEN

T1 - Sectorizing Health Conditions in Quito-Ecuador

T2 - International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2023

AU - Ortiz, Miguel

AU - Pincay, Jhonny

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

PY - 2024

Y1 - 2024

N2 - This manuscript details the conceptualization and implementation of a case study that uses operational data of a clinical laboratory to geographically sectorize health conditions in the city of Quito, Ecuador. Through the application of clustering and association rules discovering, it was possible to identify some of the ailments possibly affecting the population of Quito in different sectors of the city. After the evaluation of the results, it was concluded that although they are not enough to generalize, they provide indications about the main health issues that the population suffers from and that they might be related to the districts’ socioeconomic status. Moreover, such outcomes were considered insightful by three health experts, who manifested that they could be used as starting points for targeted health campaigns for instance.

AB - This manuscript details the conceptualization and implementation of a case study that uses operational data of a clinical laboratory to geographically sectorize health conditions in the city of Quito, Ecuador. Through the application of clustering and association rules discovering, it was possible to identify some of the ailments possibly affecting the population of Quito in different sectors of the city. After the evaluation of the results, it was concluded that although they are not enough to generalize, they provide indications about the main health issues that the population suffers from and that they might be related to the districts’ socioeconomic status. Moreover, such outcomes were considered insightful by three health experts, who manifested that they could be used as starting points for targeted health campaigns for instance.

KW - Association Discovery

KW - Clinical Data

KW - Clustering

UR - http://www.scopus.com/inward/record.url?scp=85214025478&partnerID=8YFLogxK

U2 - 10.1007/978-3-031-69228-4_32

DO - 10.1007/978-3-031-69228-4_32

M3 - Conference contribution

AN - SCOPUS:85214025478

SN - 9783031692277

T3 - Lecture Notes in Networks and Systems

SP - 481

EP - 497

BT - Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2023) - Advances in Computer Sciences - Exploring Innovations at the Intersection of Computing Technologies

A2 - Garcia, Marcelo V.

A2 - Gordón-Gallegos, Carlos

A2 - Salazar-Ramírez, Asier

A2 - Nuñez, Carlos

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 6 November 2023 through 10 November 2023

ER -

Ortiz M, Pincay J. Sectorizing Health Conditions in Quito-Ecuador: A Case Study. En Garcia MV, Gordón-Gallegos C, Salazar-Ramírez A, Nuñez C, editores, Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2023) - Advances in Computer Sciences - Exploring Innovations at the Intersection of Computing Technologies. Springer Science and Business Media Deutschland GmbH. 2024. p. 481-497. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-69228-4_32