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Clinical Decision Support System for Managing COPD-Related Readmission Risk

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Abstract

Hospital readmission is an important quality-of-care indicator that reflects challenges in quality of in-patient care and the difficulty of coordination of care after the transition back into the community. It can also be a significant financial burden, especially as it relates to Medicare and Medicaid costs now and into the future. In this study, we develop a text-mining-based methodology for providing decision support to identify patients with Chronic Obstructive Pulmonary Disease (COPD), one of the leading causes of disability and mortality worldwide, that are likely to be readmitted. The proposed methodology is tested with real-life data to demonstrate how it can be used to help healthcare providers target high-risk discharged patients to reduce readmission.

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Acknowledgements

This study was supported by the National Science Foundation grants NSF-IIP 1230661 and NSF-IPP 1444949.

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Authors and Affiliations

  1. Department of Information Technology & Operations Management, College of Business, Florida Atlantic University, Boca Raton, FL, 33431, USA

    C. Derrick Huang, Jahyun Goo & Ravi S. Behara

  2. Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, 33431, USA

    Ankur Agarwal

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  1. C. Derrick Huang
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  2. Jahyun Goo
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  4. Ankur Agarwal
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Correspondence to Jahyun Goo.

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Huang, C., Goo, J., Behara, R.S. et al. Clinical Decision Support System for Managing COPD-Related Readmission Risk. Inf Syst Front 22, 735–747 (2020). https://doi.org/10.1007/s10796-018-9881-4

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