Combining logistic regression with classification and regression tree to predict quality of care in a home health nursing data set

Huey Ming Guo*, Yea Ing Lotus Shyu, Her Kun Chang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

In this article, the authors provide an overview of a research method to predict quality of care in home health nursing data set. The results of this study can be visualized through classification an regression tree (CART) graphs. The analysis was more effective, and the results were more informative since the home health nursing dataset was analyzed with a combination of the logistic regression and CART, these two techniques complete each other. And the results more informative that more patients' characters were related to quality of care in home care. The results contributed to home health nurse predict patient outcome in case management. Improved prediction is needed for interventions to be appropriately targeted for improved patient outcome and quality of care.

Original languageEnglish
Title of host publicationConsumer-Centered Computer-Supported Care for Healthy People - Proceedings of NI 2006
Subtitle of host publicationThe 9th International Congress on Nursing Informatics
PublisherIOS Press
Pages891
Number of pages1
ISBN (Print)158603622X, 9781586036225
StatePublished - 2006
Event9th International Congress on Nursing Informatics, NI 2006 - Seoul, Korea, Republic of
Duration: 09 06 200621 06 2006

Publication series

NameStudies in Health Technology and Informatics
Volume122
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Conference

Conference9th International Congress on Nursing Informatics, NI 2006
Country/TerritoryKorea, Republic of
CitySeoul
Period09/06/0621/06/06

Keywords

  • CART
  • Data Mining
  • Home Care
  • Quality of Care

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