A Markov chain model to evaluate patient transitions in small community hospitals

Hyo Kyung Lee; Jingshan Li; Albert J. Musa; Philip A. Bain

doi:10.1109/COASE.2016.7743468

A Markov chain model to evaluate patient transitions in small community hospitals

Hyo Kyung Lee
, Jingshan Li
, Albert J. Musa
, Philip A. Bain

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

3 Citations (Scopus)

Abstract

A patient journey in the hospital may include many departments or units. Making safe and smooth transitions within the hospital is of significant importance. This paper introduces a Markov chain model to study patient transitions between emergency department, intensive or critical care unit, and hospital ward. An iteration method is presented to evaluate the performance of transition process. It is shown that such a method has a high accuracy of estimation and can be used to study patient transitions in small community hospitals. © 2016 IEEE.

Original language	English
Title of host publication	2016 IEEE International Conference on Automation Science and Engineering, CASE 2016
Publisher	IEEE Computer Society
Pages	675-680
Volume	2016-November
ISBN (Print)	9781509024094
DOIs	https://doi.org/10.1109/COASE.2016.7743468
Publication status	Published - 14 Nov 2016
Externally published	Yes
Event	2016 IEEE International Conference on Automation Science and Engineering, CASE 2016 - Fort Worth, United States Duration: 21 Aug 2016 → 24 Aug 2016

Publication series

Name	IEEE International Conference on Automation Science and Engineering
Volume	2016-November
ISSN (Print)	2161-8070
ISSN (Electronic)	2161-8089

Conference

Conference	2016 IEEE International Conference on Automation Science and Engineering, CASE 2016
Place	United States
City	Fort Worth
Period	21/08/16 → 24/08/16

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Funding

This work is supported in part by NSF Grants No. CMMI-1233807 and CMMI-1536987.

Research Keywords

iteration procedure
Markov chain
Patient transition

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10.1109/COASE.2016.7743468

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Lee, H. K., Li, J., Musa, A. J., & Bain, P. A. (2016). A Markov chain model to evaluate patient transitions in small community hospitals. In 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016 (Vol. 2016-November, pp. 675-680). Article 7743468 (IEEE International Conference on Automation Science and Engineering; Vol. 2016-November). IEEE Computer Society. https://doi.org/10.1109/COASE.2016.7743468

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Lee, HK, Li, J, Musa, AJ & Bain, PA 2016, A Markov chain model to evaluate patient transitions in small community hospitals. in 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016. vol. 2016-November, 7743468, IEEE International Conference on Automation Science and Engineering, vol. 2016-November, IEEE Computer Society, pp. 675-680, 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016, Fort Worth, United States, 21/08/16. https://doi.org/10.1109/COASE.2016.7743468

A Markov chain model to evaluate patient transitions in small community hospitals. / Lee, Hyo Kyung; Li, Jingshan; Musa, Albert J. et al.
2016 IEEE International Conference on Automation Science and Engineering, CASE 2016. Vol. 2016-November IEEE Computer Society, 2016. p. 675-680 7743468 (IEEE International Conference on Automation Science and Engineering; Vol. 2016-November).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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AU - Musa, Albert J.

AU - Bain, Philip A.

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

PY - 2016/11/14

Y1 - 2016/11/14

N2 - A patient journey in the hospital may include many departments or units. Making safe and smooth transitions within the hospital is of significant importance. This paper introduces a Markov chain model to study patient transitions between emergency department, intensive or critical care unit, and hospital ward. An iteration method is presented to evaluate the performance of transition process. It is shown that such a method has a high accuracy of estimation and can be used to study patient transitions in small community hospitals. © 2016 IEEE.

AB - A patient journey in the hospital may include many departments or units. Making safe and smooth transitions within the hospital is of significant importance. This paper introduces a Markov chain model to study patient transitions between emergency department, intensive or critical care unit, and hospital ward. An iteration method is presented to evaluate the performance of transition process. It is shown that such a method has a high accuracy of estimation and can be used to study patient transitions in small community hospitals. © 2016 IEEE.

KW - iteration procedure

KW - Markov chain

KW - Patient transition

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DO - 10.1109/COASE.2016.7743468

M3 - RGC 32 - Refereed conference paper (with host publication)

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VL - 2016-November

T3 - IEEE International Conference on Automation Science and Engineering

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BT - 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016

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ER -

Lee HK, Li J, Musa AJ, Bain PA. A Markov chain model to evaluate patient transitions in small community hospitals. In 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016. Vol. 2016-November. IEEE Computer Society. 2016. p. 675-680. 7743468. (IEEE International Conference on Automation Science and Engineering). doi: 10.1109/COASE.2016.7743468

A Markov chain model to evaluate patient transitions in small community hospitals

Abstract

Publication series

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Bibliographical note

Funding

Research Keywords

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