TY - JOUR
T1 - Modeling and Analysis of Patient Transitions in Community Hospitals
T2 - A Systems Approach
AU - Lee, Hyo Kyung
AU - Li, Jingshan
AU - Musa, Albert J.
AU - Bain, Philip A.
AU - Nelson, Kenneth
N1 - Funding Information:
Manuscript received April 6, 2016; accepted June 27, 2017. Date of publication July 27, 2017; date of current version January 15, 2020. This work was supported by the National Science Foundation under Grant CMMI-1233807 and Grant CMMI-1536987. This paper was recommended by Associate Editor A. Bargiela. (Corresponding author: Jingshan Li.) H. K. Lee and J. Li are with the Department of Industrial and Systems Engineering, University of Wisconsin–Madison, Madison, WI 53706 USA (e-mail: hlee555@wisc.edu; jingshan.li@wisc.edu).
Publisher Copyright:
© 2013 IEEE.
PY - 2020/2
Y1 - 2020/2
N2 - A patient's stay at a hospital may encompass various departments or units. Since many critical and complex problems occur at the interfaces of healthcare delivery systems, safe and efficient transitions between the departments within a hospital has significant importance. This paper presents a Markov chain-based model to study patient transitions between emergency department, intensive or critical care unit, and hospital ward in small and medium-sized community hospitals. To make the analytical study tractable, an iteration method is introduced to approximate the system performance during transitions, including direct transferring probabilities without waiting, average patient occupancy in each department, and average patient length of stay. In addition, system properties, such as monotonicity and sensitivity, are analyzed. It is shown that such a method has a high accuracy in performance estimation and can be used to study and improve patient transitions in small or medium-sized hospitals.
AB - A patient's stay at a hospital may encompass various departments or units. Since many critical and complex problems occur at the interfaces of healthcare delivery systems, safe and efficient transitions between the departments within a hospital has significant importance. This paper presents a Markov chain-based model to study patient transitions between emergency department, intensive or critical care unit, and hospital ward in small and medium-sized community hospitals. To make the analytical study tractable, an iteration method is introduced to approximate the system performance during transitions, including direct transferring probabilities without waiting, average patient occupancy in each department, and average patient length of stay. In addition, system properties, such as monotonicity and sensitivity, are analyzed. It is shown that such a method has a high accuracy in performance estimation and can be used to study and improve patient transitions in small or medium-sized hospitals.
KW - Critical care unit (CCU)
KW - emergency department (ED)
KW - iteration procedure
KW - Markov chain
KW - patient transition
KW - ward
UR - http://www.scopus.com/inward/record.url?scp=85029146352&partnerID=8YFLogxK
U2 - 10.1109/TSMC.2017.2723559
DO - 10.1109/TSMC.2017.2723559
M3 - Article
AN - SCOPUS:85029146352
VL - 50
SP - 686
EP - 699
JO - IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
JF - IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
SN - 1083-4427
IS - 2
M1 - 7994648
ER -