Using Queuing Analysis and Computer Simulation Modeling to Reduce Waiting Time in the Hospital Admitting Department

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  • Topic: Computer simulation, Patient, Queueing theory
  • Pages : 26 (5711 words )
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  • Published : April 30, 2011
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USING QUEUING ANALYSIS AND COMPUTER SIMULATION MODELING TO REDUCE WAITING TIME IN THE HOSPITAL ADMITTING DEPARTMENT Igor Georgievskiy, Zhanna Georgievskaya, William Pinney (Alcorn State University) Donald McWilliams (Texas Wesleyan University) ABSTRACT The Admitting Department is one of the most highly congested hospital services, and faces a great deal of pressure, compared with other components of the health care system. Delays in the AD system may result in difficulties of scheduling services at specialty units and decrease in patient satisfaction. This paper examines the wide-spread problem of extended waiting times for health services, in the context of the Admitting Department (AD) at a regional hospital. In the first phase of the study, a field observation was conducted to document the current operation of the AD. The authors collected actual data over a one-year period for arrivals, waiting times, and service times. These data were categorized by month, day of the week, and time of day. The data were collected for all patient groups within the AD system: outpatients, inpatients, surgical day care patients and so forth. Data were recorded for arrival into the system (waiting time 1 (WT1)), and transition from check-in to financial arrangements processing (waiting time 2 (WT2)) followed by departure from the system (to a specialty unit or out of the system). The flow charts for the admission process were developed. In the second phase of the project, a facility layout analysis provided a proposed redesign of patient flow and changed the number of work stations to alleviate choke points in the system, a proposed scheduling strategy evaluation provided new arrival rate figures, and queuing analysis and queuing simulation were employed by using Quantitative Methods System (QMS) to predict the improvements in waiting times. The third phase of the study was devoted to the building and validation of a computer simulation model of the AD using the FlexsimTM simulation software for modeling, analysis, visualization, and optimization of the patient flow within the AD. The validity of the model was established by comparison of simulation results with the data obtained during phases 1 and 2 of the study. In the fourth phase of the study, the model will be utilized to simulate the impacts of different proposed operating strategies on the waiting times and throughput rates for patients in the AD. The objective is to identify those strategies which lead to shorter waits for the patients, and therefore greater throughput rates and higher efficiency for the hospital, but without sacrificing the quality of patient care or significantly increasing costs. The fifth phase of the project will be to employ the model to gain acceptance by the hospital administration, as well as the health professionals who provide the service for the patients in the AD, that the proposed changes represent actual improvements in the quality of the health care delivery system.

BACKGROUND From queuing theory standpoint, a hospital admitting department can be viewed as a system of queues and different types of servers. A quantitative analysis of the wait time problem in an admitting department is dependent upon the identification of a methodology which recognizes the structure of the problem as that of a queuing system. Two modes of analysis are generally suggested by the structure of this type of problem: queuing models and discrete event simulations. Queuing modeling is very useful for supporting the decisions about levels of staff, resource allocation, building layout, and new policies implementation. The use of queuing analysis and simulation of various hospital departments, such as inpatient (Green, 2003), ICU (Kaplan et al, 2003), obstetrics units (Kim et al, 1999) and ED (Green et al, 2005) has been widely discussed in the literature. In some studies, researchers have generated models that were able to make accurate predictions of quantities such as...
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