PMID: 11927209Apr 3, 2002Paper

Comparing performance of multinomial logistic regression and discriminant analysis for monitoring access to care for acute myocardial infarction

Journal of Clinical Epidemiology
Monir HossainLaura A Petersen

Abstract

One way to monitor patient access to emergent health care services is to use patient characteristics to predict arrival time at the hospital after onset of symptoms. This predicted arrival time can then be compared with actual arrival time to allow monitoring of access to services. Predicted arrival time could also be used to estimate potential effects of changes in health care service availability, such as closure of an emergency department or an acute care hospital. Our goal was to determine the best statistical method for prediction of arrival intervals for patients with acute myocardial infarction (AMI) symptoms. We compared the performance of multinomial logistic regression (MLR) and discriminant analysis (DA) models. Models for MLR and DA were developed using a dataset of 3,566 male veterans hospitalized with AMI in 81 VA Medical Centers in 1994-1995 throughout the United States. The dataset was randomly divided into a training set (n = 1,846) and a test set (n = 1,720). Arrival times were grouped into three intervals on the basis of treatment considerations: <6 hours, 6-12 hours, and >12 hours. One model for MLR and two models for DA were developed using the training dataset. One DA model had equal prior probabilities, a...Continue Reading

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Citations

Dec 5, 2013·Physiological Reports·Wei ZhaoIssa F Zakeri
Aug 5, 2011·Journal of Traumatic Stress·Marie-Louise MeewisseBerthold P R Gersons
Aug 26, 2020·Journal of Orthopaedic Surgery·Mayumi SonekatsuMasaaki Mawatari

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