Welcome to the InfoSci Platform
Predicting Voluntary Participation in a Public Health Program Using a Neural Network

Predicting Voluntary Participation in a Public Health Program Using a Neural Network

George E. Heilman, Monica Cain, Russell S. Morton
Copyright: © 2008 |Volume: 3 |Issue: 2 |Pages: 11
ISSN: 1555-3396|EISSN: 1555-340X|ISSN: 1555-3396|EISBN13: 9781615202935|EISSN: 1555-340X|DOI: 10.4018/jhisi.2008040101
Cite Article Cite Article

MLA

Heilman, George E., et al. "Predicting Voluntary Participation in a Public Health Program Using a Neural Network." IJHISI vol.3, no.2 2008: pp.1-11. http://doi.org/10.4018/jhisi.2008040101

APA

Heilman, G. E., Cain, M., & Morton, R. S. (2008). Predicting Voluntary Participation in a Public Health Program Using a Neural Network. International Journal of Healthcare Information Systems and Informatics (IJHISI), 3(2), 1-11. http://doi.org/10.4018/jhisi.2008040101

Chicago

Heilman, George E., Monica Cain, and Russell S. Morton. "Predicting Voluntary Participation in a Public Health Program Using a Neural Network," International Journal of Healthcare Information Systems and Informatics (IJHISI) 3, no.2: 1-11. http://doi.org/10.4018/jhisi.2008040101

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Researchers increasingly use Artificial Neural Networks (ANNs) to predict outcomes across a broad range of applications. They frequently find the predictive power of ANNs to be as good as or better than conventional discrete choice models. This article demonstrates the use of an ANN to model a consumer’s choice to participate in North Carolina’s Maternity Care Coordination (MCC) program, a state sponsored voluntary public health service initiative. Maternal and infant Medicaid claims data and birth certificate data were collected for 59,999 births in North Carolina during the years 2000-2002. Part of this sample was used to train and test an ANN that predicts voluntary enrollment in MCC. When tested against a holdout production sample, the ANN model correctly predicted 99.69% of those choosing to participate and 100% of those choosing not to participate in the MCC program.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.