Diseño de un modelo de categorización del riesgo de reingreso para pacientes egresados de urgencias y hospitalización en clínicas de Barranquilla

The health sector is now more than a global trend; It is a topic of global interest because of its direct link with living conditions, welfare and development of persons(Law 1122 of 2007); however, the system has notorious failures in patient monitoring after care;this generated a high rate of reent...

Full description

Autores:
Altamar Maldonado, Zenaida Lucía
Martínez Solano, Cielo Isabel
Tipo de recurso:
Trabajo de grado de pregrado
Fecha de publicación:
2017
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
spa
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/335
Acceso en línea:
https://hdl.handle.net/11323/335
https://repositorio.cuc.edu.co/
Palabra clave:
Reingreso hospitalario
Caracterización
Calidad de la atención en salud
Paciente
Monitoreo externo
External monitoring
Patient
Quality of health care
Characterization
Hospital re-entry
Rights
openAccess
License
Atribución – No comercial – Compartir igual
Description
Summary:The health sector is now more than a global trend; It is a topic of global interest because of its direct link with living conditions, welfare and development of persons(Law 1122 of 2007); however, the system has notorious failures in patient monitoring after care;this generated a high rate of reentry of health care centers. This study was carried out in several stages, where the first time the characterization of the reentry of the patients graduated from the Department of Emergency and hospitalization in the subsector of clinics in the city of Barranquilla through analysis of studies and information on rates of readmissions and their causes; in addition to collecting local information (from staff and patients), studying existing evidence, boosting original research and development; allow in the second stage identify the problems generated by monitoring failures and the logical processes that are executed in order to generate a characterization of the post - care. With the diagnosis of the health system that is currently used for the external monitoring of patients and the characterization of patient readmissions to the aforementioned services, a re-entry risk categorization model will be designed for the graduates of the emergency and hospitalization Department based on the identification of the risk factors that affect their reentry to these services and the correlation risk factors and likelihood of re-entry. The applied methodology consisted in the analysis of the information presented in the SISPRO database (Comprehensive Information System for Social Protection) of the Ministry of Health, followed by the application of a test of randomness in Microsoft Excel to a population of clinics, in order to take a sample for the application of a survey to identify the risk factors that affect in the reentry of patients to the clinics of the city of Barranquilla and for the last time from a clinic in the city. In the findings derived from the results of the surveys, it is evident that operative site infections, as well as those associated with care are factors which increase the likelihood of readmission in the clinics studied. As for the re-entry reduction strategies and the external monitoring of patients by health entities, it is inferred from the results, that these do not perform an optimal follow-up to the evolution of the same after discharge, but are mostly limited to monitoring by telephone contact, thus giving rise to the probability that the patient Reenter the institution. Therefore, there is a need for health entities to implement follow-up processes for the evolution and rehabilitation of patients in a more committed, effective and assertive way to guarantee the continuous care of their health. In this investigation a statistical model was designed to measure the probability of readmissions in the hospitalization departments. The novelty of the research is the proposal of a regression application multivariate logistics to predict re-admissions of 15 days in the hospitalization departments. Our model allows us to classify patients into a category of risk. In this way, prevention plans can be created for each patient in order to reduce the probability of unplanned re-entry.The model provides enough information to analysts who are interested in managing hospital readmissions problem.The model clearly suggests that the simple and accessible parameters are useful for identifying patients at high risk of hospital readmission. Future research should study the behavior of hospital readmission in order to perform comparative analyzes and action under international framework projects.