INDUSTRIAL ENGINEERING APPLICATIONS IN HEALTH CARE SYSTEMS:APPLICATION OF QUEUING AND SIMULATION METHODOLOGIES

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APPLICATION OF QUEUING AND SIMULATION METHODOLOGIES

There are a number of examples of queues or waiting lines in health care systems where the customers must wait for service from one or more servers. The customers are usually the patients but could be hospital employees too. When patients arrive at the reception desk in a clinic for an appointment, they may have to wait in a queue for service. A patient calling a clinic on the phone for an appoint- ment may be put on hold before a clinic service representative is able to answer the call. An operating room nurse may have to wait for service at the supply desk before a supply clerk is able to handle the request for some urgently needed supply. These are all examples of queuing systems where the objective may be to determine the number of servers to obtain a proper balance between the average customer waiting time and server idle time based on cost consideration. The objective may also be to ensure that only a certain percentage of customers wait more than a predetermined amount of time (for example, that no more than 5% of the patients wait in the queue for more than five minutes.)

In simple situations, queueing models can be applied to obtain preliminary results quickly. Ap- plication of queueing models to a situation requires that the assumptions of the model be met. These assumptions relate to the interarrival time and service time probability distributions. The simplest model assumes Poisson arrivals and exponential service times. These assumptions may be approximately valid for certain queues in health care systems. Incoming phone calls to a call center for scheduling appointments have been shown to follow Poisson distribution. Usually the service times are also approximately exponentially distributed. Queueing models with Poisson arrivals and expo- nential service times have also been applied to emergency rooms for determining proper staffing of nurses and physicians (Hale 1988). From the data collected over a period of time, he was able to verify the validity of assumptions made in the model and determine the average waiting time and average number of patients waiting for service.

In situations where a simple queueing model is not applicable or a more accurate result is desired, simulation models are used. Simulation models are also used when there are complex probabilistic systems with a number of entities interacting with each other. These models are also useful during the design stage to investigate the effect of changes in various parameters in a system.

Simulation models have been extensively used in the analysis of emergency rooms (Weissberg 1977; Saunders et al. 1989). Ortiz and Etter (1990) used general-purpose simulation system (GPSS) to simulate the emergency room. They found simulation modeling to be a better approach even for simple, less complex systems because of its flexibility and capacity to investigate various alternatives. Dawson et al. (1994) used simulation models to determine optimal staffing levels in the emergency room. McGuire (1997) used a simulation model to investigate various process changes and choose a solution that significantly reduced the length of stay for patients in the emergency room.

Simulation models have also been extensively used in other areas of health care systems. Roberts and English (1981) published a bibliography of over 400 articles in literature related to simulation in health care. The Journal of the Society for Health Systems (1992b, 1997) published two issues dedicated to health care applications of simulation. Bressan et al. (1988) and Mahachek (1992) discussed generic structure for simulation in health care. Dumas and Hauser (1974) developed a simulation model to study various hospital admission policies. Kachhal et al. (1981) used GPSS to simulate outpatient internal medicine clinics in order to investigate various clinic consolidation op- tions. They used another model to determine optimal staffing for audiologists administering hearing tests ordered by ear, nose, and throat (ENT) physicians. Dumas (1984) used simulation in hospital bed planning. Hunter et al. (1987) used a model to simulate movement of surgical patients in a facility. Levy et al. (1989) developed a simulation model using SIMAN to assist in the design of a new outpatient service center. Wilt and Goddin (1989) simulated staffing needs and the flow of work in an outpatient diagnostic center. Lowery and Martin (1993) used a simulation model in a critical care environment. Cirillo and Wise (1996) used simulation models to test the impact of changes in a radiology department. Schroyer (1997) used a simulation model to plan an ambulatory surgery facility. Benneyan (1997) conducted a simulation study of a pediatric clinic to reduce patient wait during a visit to the clinic.

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