DocumentCode
243804
Title
Pathway-Finder: An Interactive Recommender System for Supporting Personalized Care Pathways
Author
Rui Liu ; Srinivasan, Raj Velamur ; Zolfaghar, Kiyana ; Si-Chi Chin ; Roy, Senjuti Basu ; Hasan, Aftab ; Hazel, David
Author_Institution
Center for Data Sci., UW Tacoma, Tacoma, WA, USA
fYear
2014
fDate
14-14 Dec. 2014
Firstpage
1219
Lastpage
1222
Abstract
Clinical pathways define the essential component of the complex care process, with the objective to optimize patient outcomes and resource allocation. Clinical pathway analysis has gained increased attention in order to augment the patient treatment process. In this demonstration paper, we propose Pathway-Finder, an interactive recommender system to visually explore and discover clinical pathways. The interactive web service efficiently collects and displays patient information in a meaningful way to support an effective personalized treatment plan. Pathway-Finder implements a Bayesian Network to discover causal relationships among different factors. To support real-time recommendation and visualization, a key-value structure has been implemented to traverse the Bayesian Network faster. Additionally, Pathway-Finder is a cloud based web service hosted on Microsoft Azure which enables the health providers to access the system without the need to deploy analytics infrastructure. We demonstrate Pathway-Finder to interactively recommend personalized interventions to minimize 30-day readmission risk for Heart Failure (HF).
Keywords
Web services; belief networks; cloud computing; data visualisation; medical information systems; patient care; patient treatment; recommender systems; resource allocation; Bayesian network; Microsoft Azure; Pathway-Finder; causal relationship; clinical pathway analysis; cloud based Web service; complex care process; health provider; heart failure; interactive Web service; interactive recommender system; patient information; patient outcome; patient treatment process; personalized care pathway; personalized treatment plan; real-time recommendation; real-time visualization; resource allocation; Algorithm design and analysis; Bayes methods; Diseases; Heart; Medical treatment; Probability distribution; Real-time systems; bayesian network; heart failure; intervention recommendation; risk of readmission;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining Workshop (ICDMW), 2014 IEEE International Conference on
Conference_Location
Shenzhen
Print_ISBN
978-1-4799-4275-6
Type
conf
DOI
10.1109/ICDMW.2014.37
Filename
7022738
Link To Document