Application of logistic regression for the prediction of demand by medical specialty in hospital outpatient consultation

• Autores: Aquino Arcata, Rene, Cuevas Machaca, Ronald, Godoy Montoya, Luis, Rodríguez Puma, Heber
• Formato: artículo
• Fecha de Publicación: 2021
• Institución: Universidad La Salle
• Repositorio: Revistas - Universidad La Salle
• Lenguaje: español
• OAI Identifier: oai:ojs.revistas.ulasalle.edu.pe:article/45
• Enlace del recurso: https://revistas.ulasalle.edu.pe/innosoft/article/view/45; https://doi.org/10.48168/innosoft.s6.a45; https://purl.org/42411/s6/a45; https://n2t.net/ark:/42411/s6/a45
• Nivel de acceso: acceso abierto
• Materia: medical care; covid-19; prediction; logistic regression; atenciones médicas; predicción; regresión logística

In this work, the analysis of the information produced by the care of patients in the outpatient service was carried out. Studies have been reviewed that are related to the possible methodologies to be used, before choosing one in particular. At the Regional Hospital of Moquegua, since the beginning of the health emergency due to Covid-19, care in the outpatient service was suspended, that is, from March 2020 to June 2021 there is no information on how much the demand would have been by specialty in said service. The objective of the work is to predict, based on age and sex variables, the number of female patients who will request an appointment for outpatient specialties, in a period of time. To solve the problem, the logistic regression technique was used, which initially allowed us to classify and determine the importance group on the basis of which our objective is oriented, taking sex and age as relevant variables. The results obtained from the initial procedure of the model did not show real correspondence to the expected prediction. The conclusions determine that the proposed model requires the inclusion of other input variables