Predictive Model Based on Machine Learning to Decrease Patient Attrition in Health Care Institutions in Lima Using Python (#248)
Read ArticleDate of Conference
July 17-19, 2024
Published In
"Sustainable Engineering for a Diverse, Equitable, and Inclusive Future at the Service of Education, Research, and Industry for a Society 5.0."
Location of Conference
Costa Rica
Authors
Ovalle Paulino, Christian
Abstract
The present research addresses one of the main problems that prevent health problems in the country from being combated, identifying it as a significant challenge in health management. For this reason, it is necessary to generate a detection and/or prevention tool for these cases, so a predictive model is proposed to anticipate patients prone to drop out of the services of a health center. The research focuses on the Sanna El Golf clinic, where, by means of a predictive analysis, a 67% of assertiveness is obtained as a result, this approach shows substantial benefits for the clinic and highlights its contribution to meet the objectives set. In addition, the proposed model is positioned as a key tool in the prevention of medical attrition, identifying it as a significant challenge in health management.