scholarly journals The Impact of One-Dose Package of Medicines on Patient Waiting Time in Dispensing Pharmacy: Application of a Discrete Event Simulation Model

2018 ◽  
Vol 41 (3) ◽  
pp. 409-418
Author(s):  
Daisuke Furushima ◽  
Hiroshi Yamada ◽  
Michiko Kido ◽  
Yuko Ohno
Keyword(s):  
Simulation Model ◽  
Discrete Event Simulation ◽  
Waiting Time ◽  
Discrete Event ◽  
Event Simulation ◽  
Discrete Event Simulation Model ◽  
Patient Waiting Time ◽  
The Impact ◽  
Patient Waiting

Improving patient waiting time of centralized front office service in a regional hub hospital using the discrete event simulation model

2020 ◽  
Vol 28 (5) ◽  
pp. 487-494
Author(s):  
D. Cocchi ◽  
E. Ciagli ◽  
A. Ancora ◽  
P. Tortoli ◽  
C. Carpini ◽  
...  
Keyword(s):  
Simulation Model ◽  
Discrete Event Simulation ◽  
Waiting Time ◽  
Waiting Times ◽  
Discrete Event ◽  
University Hospital ◽  
Event Simulation ◽  
Discrete Event Simulation Model ◽  
Front Office ◽  
Patient Waiting

BACKGROUND: Today, hospital rankings are based not only on basic clinical indicators, but even on quality service indicators such as patient waiting times. Improving these indicators is a very important issue for hospital management, so finding a solution to achieve it in a simple and effective way is one of the greatest goals. OBJECTIVES: The aim of this article is to evaluate the use of a discrete event simulation model to improve healthcare processes and reduce waiting time of patients and hospital costs. METHODS: The case study proposed in this paper is the reorganization of non-clinical front office operation for the patients (i.e. booking of exams, delivering medical reports, etc.) of the Careggi University Hospital of Florence, to optimize the utilization of the human resources and to improve performances of the process. RESULTS: The development and validation of the model was made according to an analysis of real processes and data, pre and post implementation of model outcomes. The new organization shows a decrease of waiting times from an average value of 10 minutes and 37 seconds to 5 minutes and 57 seconds (-44%). CONCLUSIONS: This paper shows that discrete event simulation could be a precise, cost-limited tool to optimize hospital processes and performance.

scholarly journals Designing optimal COVID-19 testing stations locally: A discrete event simulation model applied on a university campus

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253869
Author(s):  
Michael Saidani ◽  
Harrison Kim ◽  
Jinju Kim
Keyword(s):  
Simulation Model ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Daily Basis ◽  
Health Crisis ◽  
Event Simulation ◽  
Discrete Event Simulation Model ◽  
Rapid Result ◽  
The Usa ◽  
The Impact

Providing sufficient testing capacities and accurate results in a time-efficient way are essential to prevent the spread and lower the curve of a health crisis, such as the COVID-19 pandemic. In line with recent research investigating how simulation-based models and tools could contribute to mitigating the impact of COVID-19, a discrete event simulation model is developed to design optimal saliva-based COVID-19 testing stations performing sensitive, non-invasive, and rapid-result RT-qPCR tests processing. This model aims to determine the adequate number of machines and operators required, as well as their allocation at different workstations, according to the resources available and the rate of samples to be tested per day. The model has been built and experienced using actual data and processes implemented on-campus at the University of Illinois at Urbana-Champaign, where an average of around 10,000 samples needed to be processed on a daily basis, representing at the end of August 2020 more than 2% of all the COVID-19 tests performed per day in the USA. It helped identify specific bottlenecks and associated areas of improvement in the process to save human resources and time. Practically, the overall approach, including the proposed modular discrete event simulation model, can easily be reused or modified to fit other contexts where local COVID-19 testing stations have to be implemented or optimized. It could notably support on-site managers and decision-makers in dimensioning testing stations by allocating the appropriate type and quantity of resources.

Assessing Pilot Workload in Single-Pilot Operations with Advanced Autonomy

2016 ◽  
Vol 60 (1) ◽  
pp. 675-679 ◽  
Author(s):  
Alexander J. Stimpson ◽  
Jason C. Ryan ◽  
Mary L. Cummings
Keyword(s):  
Simulation Model ◽  
Detailed Analysis ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Military Aircraft ◽  
Event Simulation ◽  
Discrete Event Simulation Model ◽  
High Workload ◽  
Point To Point ◽  
The Impact

The proposed transition to single-pilot operations (SPO) in commercial and military aircraft has motivated the development of advanced autonomy systems. However, a detailed analysis of the impact of advanced autonomy on pilot workload through various phases of flight and contingency scenarios has not been conducted. To this end, this paper presents the development of the Pilot-Autonomy Workload Simulation (PAWS), a discrete event simulation model that allows the investigation of pilot workload under a variety of advanced autonomy capabilities and scenarios. Initial utilization results from PAWS of nominal and off-nominal point-to-point missions demonstrate that the workload for a single pilot assisted by advanced autonomy varies considerably over different phases of flight and various contingencies. These results suggest that advanced autonomy to offset pilot workload is not needed for low-workload phases, but could be critical during periods of high workload.

Using lean techniques and discrete-event simulation for performance improvement in an outpatient clinic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kudret Demirli ◽  
Abdulqader Al Kaf ◽  
Mecit Can Emre Simsekler ◽  
Raja Jayaraman ◽  
Mumtaz Jamshed Khan ◽  
...  
Keyword(s):  
Health Care ◽  
Discrete Event Simulation ◽  
Waiting Time ◽  
Outpatient Clinic ◽  
Waiting Times ◽  
Discrete Event ◽  
Content Type ◽  
Event Simulation ◽  
Patient Waiting Time ◽  
Patient Waiting

Purpose Increased demand and the pressure to reduce health-care costs have led to longer waiting time for patients to make appointments and during the day of hospital visits. The purpose of this study is to identify opportunities to reduce waiting time using lean techniques and discrete-event simulation (DES). Design/methodology/approach A five-step procedure is proposed to facilitate the effective utilization of lean and DES to improve the performance of the Otolaryngology Head and Neck Surgery Outpatient Clinic at Cleveland Clinic Abu Dhabi. While lean techniques were applied to reduce the potential sources of waste by aligning processes, a DES model was developed to validate the proposed solutions and plan patient arrivals under dynamic conditions and different scenarios. Findings Aligning processes resulted in an efficient patient flow reducing both waiting times. DES played a complementary role in verifying lean solutions under dynamic conditions, helping to plan the patient arrivals and striking a balance between the waiting times. The proposed solutions offered flexibility to improve the clinic capacity from the current 176 patients up to 479 (without violating the 30 min waiting time policy) or to reduce the patient waiting time during the visit from the current 33 min to 4.5 min (without violating the capacity goal of 333 patients). Research limitations/implications Proposing and validating lean solutions require reliable data to be collected from the clinic and such a process could be laborious as data collection require patient and resource tracing without interfering with the regular functions of the clinic. Practical implications The work enables health-care managers to conveniently conduct a trade-off analysis and choose a suitable inter-arrival time – for every physician – that would satisfy their objectives between resource utilization (clinic capacity) and average patient waiting time. Social implications Successful implementation of lean requires a supportive and cooperative culture from all stakeholders involved. Originality/value This study presents an original and detailed application of lean techniques with DES to reduce patient waiting times. The adopted approach in this study could be generalized to other health-care settings with similar objectives.

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