Optimizing the Performance of Magnetic Resonance Imaging Department Using Queuing Theory and Simulation

Bahadori, Mohammadkarim; Teymourzadeh, Ehsan; Hosseini, Seyed Hadi; Ravangard, Ramin

doi:10.17795/semj43958

Cited by 2 publications

(3 citation statements)

References 28 publications

(26 reference statements)

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“…Another study conducted a DES of the addition of one dosimetrist and reported a 6.55% reduction in the average wait time for radiation treatment in a radiation oncology clinic and an increase in the proportion of patients (84.92%) who would receive treatment within 14 working days. In another DES study, the addition of one MRI scanner and one radiation technologist at a military hospital in Iran resulted in an improvement in the medical personnel’s productivity and the elimination of patient wait time for turn-taking until admission [ 23 ]. In a Canadian study that employed a DES model, increasing the number of physician visits and sleep therapists reduced the wait times for examinations in a sleep therapy center by approximately 28 days [ 24 ].…”

Section: Literature Reviewmentioning

confidence: 99%

“…By contrast, simulations allow for the modeling of real-world environments and systems through the use of software, which enables a proposed solution to be implemented in a simulated model without affecting the current situation and without investment in resources. According to existing simulation-based evaluation studies, three strategies can be applied to shorten long wait times and increase the number of MRI department services that are provided: investing in additional workforce and related resources [7,[23][24][25]; minimizing the idle time of available scanners, rooms, and physicians involved in MRI examinations [8,19,26]; and minimizing the operation time of current services [9].…”

Section: Application Of Simulation To Improve Patient Wait Timesmentioning

confidence: 99%

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Simulation and evaluation of increased imaging service capacity at the MRI department using reduced coil-setting times

Sun¹,

Wu²,

Guo³

et al. 2023

PLoS ONE

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The wait times for patients from their appointments to receiving magnetic resonance imaging (MRI) are usually long. To reduce this wait time, the present study proposed that service time wastage could be reduced by adjusting MRI examination scheduling by prioritizing patients who require examinations involving the same type of coil. This approach can reduce patient wait times and thereby maximize MRI departments’ service times. To simulate an MRI department’s action workflow, 2,447 MRI examination logs containing the deidentified information of patients and radiation technologists from the MRI department of a medical center were used, and a hybrid simulation model that combined discrete-event and agent-based simulations was developed. The experiment was conducted in two stages. In the first stage, the service time was increased by adjusting the examination schedule and thereby reducing the number of coil changes. In the second stage, the maximum number of additional patients that could be examined daily was determined. The average number of coil changes per day for the four MRI scanners of the aforementioned medical center was reduced by approximately 27. Thus, the MRI department gained 97.17 min/d, which enabled them to examine three additional patients per month. Consequently, the net monthly income of the hospital increased from US$17,067 to US$30,196, and the patient wait times for MRI examinations requiring the use of flexible torso and head, shoulder, 8-inch head, and torso MRI coils were shortened by 6 d and 23 h, 2 d and 15 h, 2 d and 9 h, and 16 h, respectively. Adjusting MRI examination scheduling by prioritizing patients that require the use of the same coil could reduce the coil-setting time, increase the daily number of patients who are examined, increase the net income of the MRI department, and shorten patient wait times for MRI examinations. Minimizing the operating times of specific examinations to maximize the number of services provided per day does not require additional personnel or resources. The results of the experimental simulations can be used as a reference by radiology department managers designing scheduling rules for examination appointments.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Application Of Simulation To Improve Patient Wait Timesmentioning

confidence: 99%

Simulation and evaluation of increased imaging service capacity at the MRI department using reduced coil-setting times

Sun¹,

Wu²,

Guo³

et al. 2023

PLoS ONE

View full text Add to dashboard Cite

show abstract

“…The exact performance indicators that were calculated in their study include the average number of patients referred to the pharmacy and the system utilization rate. Bahadori, Teymourzadeh, Hosseini, & Ravangard (2017) targeted the performance optimization of a magnetic resonance imaging (MRI) department in a hospital using queuing theory and simulation. For assessing the performance measures pertaining to the queuing model (including the queue length and average waiting time), they considered the different workstations that the patients face in this department.…”

Section: Related Workmentioning

confidence: 99%

Specifications of a Queuing Model-Driven Decision Support System for Predicting the Healthcare Performance Indicators Pertaining to the Patient Flow

Fadelelmoula

2022

International Journal of Decision Support System Technology

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This article has developed specifications for a new model-driven decision support system (DSS) that aids the key stakeholders of public hospitals in estimating and tracking a set of crucial performance indicators pertaining to the patients flow. The developed specifications have considered several requirements for ensuring an effective system, including tracking the performance indicator on the level of the entire patients flow system, paying attention to the dynamic change of the values of the indicator’s parameters, and considering the heterogeneity of the patients. According to these requirements, the major components of the proposed system, which include a comprehensive object-based queuing model and an object-oriented database, have been specified. In addition to these components, the system comprises the equations that produce the required predictions. From the system output perspective, these predictions act as a foundation for evaluating the performance indicators as well as developing policies for managing the patients flow in the public hospitals.

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Optimizing the Performance of Magnetic Resonance Imaging Department Using Queuing Theory and Simulation

Abstract: Background: The diagnostic services such as Magnetic Resonance Imaging (MRI) require advanced and costly technologies; and making the right managerial decisions to reduce patients' waiting time and increase employees' productivity in providing such services is essential.

Cited by 2 publications

References 28 publications

Simulation and evaluation of increased imaging service capacity at the MRI department using reduced coil-setting times

Simulation and evaluation of increased imaging service capacity at the MRI department using reduced coil-setting times

Specifications of a Queuing Model-Driven Decision Support System for Predicting the Healthcare Performance Indicators Pertaining to the Patient Flow

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