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A Technique to Exploit Free-Form Notes to Predict Customer Churn

A Technique to Exploit Free-Form Notes to Predict Customer Churn

Gregory W. Ramsey, Sanjay Bapna
Copyright: © 2014 |Volume: 4 |Issue: 1 |Pages: 16
ISSN: 1947-3133|EISSN: 1947-3141|EISBN13: 9781466653290|DOI: 10.4018/ijcmam.2014010101
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MLA

Ramsey, Gregory W., and Sanjay Bapna. "A Technique to Exploit Free-Form Notes to Predict Customer Churn." IJCMAM vol.4, no.1 2014: pp.1-16. http://doi.org/10.4018/ijcmam.2014010101

APA

Ramsey, G. W. & Bapna, S. (2014). A Technique to Exploit Free-Form Notes to Predict Customer Churn. International Journal of Computational Models and Algorithms in Medicine (IJCMAM), 4(1), 1-16. http://doi.org/10.4018/ijcmam.2014010101

Chicago

Ramsey, Gregory W., and Sanjay Bapna. "A Technique to Exploit Free-Form Notes to Predict Customer Churn," International Journal of Computational Models and Algorithms in Medicine (IJCMAM) 4, no.1: 1-16. http://doi.org/10.4018/ijcmam.2014010101

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Abstract

As healthcare costs rise, hospitals are seeking ways to improve operations. This paper examines the usefulness of free-form notes to solve a classification problem commonly associated with customer churn. The authors show that classifiers which incorporate free-form notes, using natural language processing techniques, are up to 9% more accurate than classifiers that are solely developed using structured data. The authors suggest that hospitals and chronic disease management clinics can use structured data and free-form notes from electronic health records to predict which patients are likely to cease receiving care from their facilities. Classification tools for predicting patient churn are of interest to hospital administrators; such information can aid in resource planning and facilitate smoother handoffs between care providers.

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