@inproceedings{2b9a46fd6674469f8a9818196a9bb4d3,
title = "Incentive-based optimal intervention policy to reduce hospital readmissions for COPD patients",
abstract = "This paper introduces an optimization model to support decision making for selection of appropriate incentive-based interventions to reduce readmissions of patients with chronic obstructive pulmonary disease (COPD). Such a model can be used to identify the optimal incentive policies to encourage patients taking appropriate interventions so that the readmission risk can be minimized under an incentive budget constraint. Closed formulas are derived under various budget scenarios and managerial insights are discussed to guide intervention implementation. The results of this work provide a quantitative tool to support hospitals planning of intervention activities.",
keywords = "Chronic obstructive pulmonary disease (COPD), incentive, intervention, optimal policy, readmission",
author = "Sujee Lee and Xiang Zhong and Lee, {Hyo Kyung} and Cong Zhao and Bain, {Philip A.} and Tammy Kundinger and Craig Sommers and Christine Baker and Jingshan Li",
note = "Funding Information: This work is supported in part by NSF Grant No. CMMI-1536987. Funding Information: ACKNOWLEDGEMENT The authors thank to the help of Jesus Chavez Mees, Henry Rose, and Bo Zhang of University of Wisconsin-Madison and the support from staffs of St. Mary{\textquoteright}s Hospital. Publisher Copyright: {\textcopyright} 2017 IEEE.; 13th IEEE Conference on Automation Science and Engineering, CASE 2017 ; Conference date: 20-08-2017 Through 23-08-2017",
year = "2017",
month = jul,
day = "1",
doi = "10.1109/COASE.2017.8256164",
language = "English",
series = "IEEE International Conference on Automation Science and Engineering",
publisher = "IEEE Computer Society",
pages = "562--567",
booktitle = "2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017",
}