Open AccessPredictive Modelling for Hospital Readmission Risk in the Philippines
Author(s) -
Junar Arciete Landicho,
Vatcharaporn Esichaikul,
Roy Magdugo Sasil
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/864/1/012061
Subject(s) - medicine , logistic regression , copd , cohort , myocardial infarction , emergency medicine , hospital readmission , heart failure , pulmonary disease , pneumonia , cohort study , intensive care medicine
Predictive models have been developed over the years to identify patients at risk of readmission. The goal of this study is to identify the risk factors associated to a patient’s readmission within one year in the cohort study including acute myocardial infarction (AMI), Heart Failure (HF), Chronic Obstructive Pulmonary Disease (COPD) and Pneumonia (PN) in a reputed Philippine hospital. Four predictive models were used and evaluated using performance metrics. The study found Logistic Regression as the most performing model in most of the cohort studies. There are 6 to 8 variables significantly associated with the readmission of high-risk patients.