scholarly journals Analysis of the Installed Productive Capacity in a Medical Angiography Room through Discrete Event Simulation

Processes ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 660
Author(s):  
Félix Badilla-Murillo ◽  
Bernal Vargas-Vargas ◽  
Oscar Víquez-Acuña ◽  
Justo García-Sanz-Calcedo
Keyword(s):  
Resource Utilization ◽  
Discrete Event Simulation ◽  
Current System ◽  
Waiting Times ◽  
Continuous Process ◽  
Discrete Event ◽  
Computer Software ◽  
Productive Capacity ◽  
Continuous Process Improvement ◽  
Event Simulation

The installed productive capacity of a healthcare center’s equipment limits the efficient use of its resources. This paper, therefore, analyzes the installed productive capacity of a hospital angiography room and how to optimize patient demand. For this purpose, a Discrete Event Simulation (DES) model based on historical variables from the current system was created using computer software. The authors analyzed 2044 procedures performed between 2014 and 2015 in a hospital in San José, Costa Rica. The model was statistically validated to determine that it does not significantly differ from the current system, considering the DMAIC stages for continuous process improvement. In the current scenario, resource utilization is 0.99, and the waiting list increases every month. The results showed that the current capacity of the service could be doubled, and that resource utilization could be reduced to 0.64 and waiting times by 94%. An increase in service efficiency could be achieved by shortening maximum waiting times from 6.75 days to 3.70 h. DES simulation, therefore, allows optimizing of the use of healthcare systems’ resources and hospital management.

scholarly journals Modelling patient flows and resource use within a sexual health clinic through discrete event simulation to inform service redesign

BMJ Open ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. e037084
Author(s):  
Syed Mohiuddin ◽  
Rebecca Gardiner ◽  
Megan Crofts ◽  
Peter Muir ◽  
Jonathan Steer ◽  
...  
Keyword(s):  
Health Services ◽  
Discrete Event Simulation ◽  
Resource Use ◽  
Current System ◽  
Waiting Times ◽  
Discrete Event ◽  
Event Simulation ◽  
Asymptomatic Patients ◽  
Service Redesign ◽  
Delivery Of Health Services

ObjectivesContinuous improvement in the delivery of health services is increasingly being demanded in the UK at a time when budgets are being cut. Simulation is one approach used for understanding and assessing the likely impact of changes to the delivery of health services. However, little is known about the usefulness of simulation for analysing the delivery of sexual health services (SHSs). We propose a simulation method to model and evaluate patient flows and resource use within an SHS to inform service redesign.MethodsWe developed a discrete event simulation (DES) model to identify the bottlenecks within the Unity SHS (Bristol, UK) and find possible routes for service improvement. Using the example of the introduction of an online service for sexually transmitted infection (STI) and HIV self-sampling for asymptomatic patients, the impact on patient waiting times was examined as the main outcome measure. The model included data such as patient arrival time, staff availability and duration of consultation, examination and treatment. We performed several sensitivity analyses to assess uncertainty in the model parameters.ResultsWe identified some bottlenecks under the current system, particularly in the consultation and treatment queues for male and female walk-in patients. Introducing the provision of STI and HIV self-sampling alongside existing services decreased the average waiting time (88 vs 128 min) for all patients and reduced the cost of staff time for managing each patient (£72.64 vs £88.74) compared with the current system without online-based self-sampling.ConclusionsThe provision of online-based STI and HIV self-sampling for asymptomatic patients could be beneficial in reducing patient waiting times and the model highlights the complexities of using this to cut costs. Attributing recognition for any improvement requires care, but DES modelling can provide valuable insights into the design of SHSs ensuing in quantifiable improvements. Extension of this method with the collection of additional data and the construction of more informed models seems worthwhile.

scholarly journals Continuous process improvement implementation framework using multi-objective genetic algorithms and discrete event simulation

2019 ◽  
Vol 25 (5) ◽  
pp. 1020-1039 ◽  
Author(s):  
Parminder Singh Kang ◽  
Rajbir Singh Bhatti
Keyword(s):  
Discrete Event Simulation ◽  
Process Improvement ◽  
Continuous Process ◽  
Discrete Event ◽  
Buffer Size ◽  
Size Optimization ◽  
Continuous Process Improvement ◽  
Content Type ◽  
Event Simulation ◽  
Job Sequencing

Purpose Continuous process improvement is a hard problem, especially in high variety/low volume environments due to the complex interrelationships between processes. The purpose of this paper is to address the process improvement issues by simultaneously investigating the job sequencing and buffer size optimization problems. Design/methodology/approach This paper proposes a continuous process improvement implementation framework using a modified genetic algorithm (GA) and discrete event simulation to achieve multi-objective optimization. The proposed combinatorial optimization module combines the problem of job sequencing and buffer size optimization under a generic process improvement framework, where lead time and total inventory holding cost are used as two combinatorial optimization objectives. The proposed approach uses the discrete event simulation to mimic the manufacturing environment, the constraints imposed by the real environment and the different levels of variability associated with the resources. Findings Compared to existing evolutionary algorithm-based methods, the proposed framework considers the interrelationship between succeeding and preceding processes and the variability induced by both job sequence and buffer size problems on each other. A computational analysis shows significant improvement by applying the proposed framework. Originality/value Significant body of work exists in the area of continuous process improvement, discrete event simulation and GAs, a little work has been found where GAs and discrete event simulation are used together to implement continuous process improvement as an iterative approach. Also, a modified GA simultaneously addresses the job sequencing and buffer size optimization problems by considering the interrelationships and the effect of variability due to both on each other.

scholarly journals Simulation modeling and analysis of primary health center operations

SIMULATION ◽  
2021 ◽  
pp. 003754972110309
Author(s):  
Mohd Shoaib ◽  
Varun Ramamohan
Keyword(s):  
Resource Utilization ◽  
Waiting Times ◽  
Discrete Event ◽  
Simulation Models ◽  
Modeling And Analysis ◽  
Healthcare Facilities ◽  
Event Simulation ◽  
Analytical Approximations ◽  
Primary Health ◽  
Generic Modeling

We present discrete-event simulation models of the operations of primary health centers (PHCs) in the Indian context. Our PHC simulation models incorporate four types of patients seeking medical care: outpatients, inpatients, childbirth cases, and patients seeking antenatal care. A generic modeling approach was adopted to develop simulation models of PHC operations. This involved developing an archetype PHC simulation, which was then adapted to represent two other PHC configurations, differing in numbers of resources and types of services provided, encountered during PHC visits. A model representing a benchmark configuration conforming to government-mandated operational guidelines, with demand estimated from disease burden data and service times closer to international estimates (higher than observed), was also developed. Simulation outcomes for the three observed configurations indicate negligible patient waiting times and low resource utilization values at observed patient demand estimates. However, simulation outcomes for the benchmark configuration indicated significantly higher resource utilization. Simulation experiments to evaluate the effect of potential changes in operational patterns on reducing the utilization of stressed resources for the benchmark case were performed. Our analysis also motivated the development of simple analytical approximations of the average utilization of a server in a queueing system with characteristics similar to the PHC doctor/patient system. Our study represents the first step in an ongoing effort to establish the computational infrastructure required to analyze public health operations in India and can provide researchers in other settings with hierarchical health systems, a template for the development of simulation models of their primary healthcare facilities.

Discrete Event Simulation Of The COVID-19 Sample Collection Point Operation

2021 ◽  
Author(s):  
Martina Kuncova ◽  
Katerina Svitkova ◽  
Alena Vackova ◽  
Milena Vankova
Keyword(s):  
Discrete Event Simulation ◽  
Waiting Times ◽  
Discrete Event ◽  
Real Data ◽  
Simulation Software ◽  
Sample Collection ◽  
The Real ◽  
Event Simulation ◽  
Collection Process ◽  
Collection Point

The year 2020 was very challenging for everyone due to the COVID-19 pandemic. Many people turn their lives upside down from day to day. Politicians had to impose completely unprecedented measures, and doctors immediately had to adapt to the huge influx of patients and the massive demand for testing. Of course, not all processes could be planned completely efficiently, given that the situation literally changes from minute to minute, but sometimes better planning could improve the real processes. This contribution deals with the application of simulation software SIMUL8 to the analysis of the COVID-19 sample collection process in a drive-in point in a hospital. The main aim is to create a model based on the real data and then to find out the suitable number of other staff (medics) helping a doctor during the process to decrease the number of unattended patients and their waiting times.

scholarly journals Employment of Emergency Advanced Nurses of Turkey: A Discrete-Event Simulation Application

Processes ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 48 ◽  
Author(s):  
Abdulkadir Atalan ◽  
Cem Donmez
Keyword(s):  
Length Of Stay ◽  
Discrete Event Simulation ◽  
Emergency Services ◽  
Treatment Time ◽  
Waiting Times ◽  
Discrete Event ◽  
Weekly Basis ◽  
Event Simulation ◽  
Number Of Patients ◽  
Efficiency Rate

In the present study, problems in emergency services (ESs) were dealt with by analyzing the working system of ESs in Turkey. The purpose of this study was to reduce the waiting times spent in hospitals by employing advanced nurses (ANs) to treat patients who are not urgent, or who may be treated as outpatients in ESs. By applying discrete-event simulation on a 1/24 (daily) and 7/24 (weekly) basis, and by employing ANs, it was determined that the number of patients that were treated increased by 26.71% on a 1/24 basis, and by 15.13% on a 7/24 basis. The waiting time that was spent from the admission to the ES until the treatment time decreased by 38.67% on a 1/24 basis and 53.66% on a 24/7 basis. Similarly, the length of stay was reduced from 82.46 min to 53.97 min in the ES. Among the findings, it was observed that the efficiency rate of the resources was balanced by the employment of ANs, although it was not possible to obtain sufficient efficiency from the resources used in the ESs prior to the present study.

scholarly journals Performance Measurement and Improvement of Healthcare Service Using Discrete Event Simulation in Bahir Dar Clinic

2020 ◽  
Author(s):  
Aregawi yemane Meresa ◽  
Hagazi Abrha Heniey ◽  
Kidane Gidey
Keyword(s):  
Performance Measurement ◽  
Resource Utilization ◽  
Discrete Event Simulation ◽  
Healthcare Service ◽  
Service System ◽  
Discrete Event ◽  
Bahir Dar ◽  
Work In Progress ◽  
Event Simulation ◽  
Service Efficiency

This paper deals with the service performance analysis and improvement using discrete event simulation has been used. The simulation of the heath care has been done by arena master development 14-version software. The performance measurement for this study are patients output, service rate, service efficiency and it is directly related to waiting time of patients in each service station, work in progress, resource utilization.Simulation model was building for Bahir Dar clinic and then, prepared the proposed model for the system. Based on the simulation model run result, the output of the existing healthcare service system is low due to presence of bottlenecks on the service system. Moreover, the station with the largest queue and high resource utilization are identified as a bottleneck. The bottlenecks, which have identified are reduced by using reassigning the existing resources and add new resources and merging the similar services, which has under low resource utilization (nurses). Finally, the researchers have proposed a developed model from different scenarios. Moreover, the best scenario is developed by combining scenario 2 and 3. And then, service efficiency of the healthcare has increased by 9.86 percent, the work in progress (WIP) are reduced by 3 patients from the system and the service capacity of the system is increased 34 to 40 patients per day due to the reduction of bottleneck stations.

scholarly journals Discrete event simulation for problem solving in the context of an emergency department

2020 ◽  
Vol 11 (5) ◽  
pp. 1515
Author(s):  
Letícia Ali Figueiredo Ferreira ◽  
Igor Leão dos Santos ◽  
Ana Carla De Souza Gomes dos Santos ◽  
Augusto Da Cunha Reis
Keyword(s):  
Length Of Stay ◽  
Discrete Event Simulation ◽  
Waiting Times ◽  
Discrete Event ◽  
Saturation Point ◽  
Event Simulation ◽  
Emergency Care System ◽  
Patient Arrival ◽  
The Subject

Emergency departments (ED) are responsible for the immediate care and stabilization of patients in critical health conditions. Several factors have caused overcrowding in the emergency care system, but the variability of patient arrival and the triage process requires special attention. The criticality of these components and their configuration directly impact the waiting times, length of stay and quality of service, being the subject of several studies. So, this paper aims to understand by means of Discrete Event Simulation how ED works with the variation of patient arrival and how this variation highlights the bottlenecks of the triage process. Varying the patient arriving interval between 0.1 and 7.6 in a 4-hour scenario,  the system saturation point was established in β = 1.1. Besides, with the variation in the number of triages points, a considerable decrease in the total length of stay spent and the waiting times were noticed, mainly when there was two triage points operating simultaneously.

scholarly journals COMPARING SCHEDULING APPOINTMENT RULES PERFORMANCE IN HEALTH CARE UNITS: A DISCRETE EVENT SIMULATION APPROACH

2021 ◽  
Vol 16 (1) ◽  
pp. 28-41
Author(s):  
Thiago Nunes Klojda ◽  
Antônio Pedro de Britto Pereira Fortuna ◽  
Bianca Menezes Araujo ◽  
Daniel Bouzon Nagem Assad ◽  
Thaís Spiegel
Keyword(s):  
Health Care ◽  
Discrete Event Simulation ◽  
Health Care Systems ◽  
Waiting Times ◽  
Discrete Event ◽  
Idle Time ◽  
Event Simulation ◽  
Care Systems ◽  
Demand Scenario ◽  
Patient Waiting

Health care systems are affected by sudden increases in demand that can be generated by factors such as natural disasters, terrorist attacks, epidemics, among others. Patient demand can be divided between scheduled and walk-in and, in pandemic scenarios, both of them must be managed in order to avoid higher patient waiting times or number in queue. A discrete event simulation model is proposed in order to evaluate critical indicators like: patient waiting times, number in queue, resource utilization (doctors), using four different patient schedule appointment rules. In this study it was also considered patients impunctuality, walk-in patients and no-show in different scenarios. The best schedule appointment rules for each demand scenario were evaluated. After comparing six performance indicators, four schedule appointment rules in nine different scenarios it was found that the most known scheduling rule had the lowest queue sizes at scenarios with low or no walk-in patients, whereas, as the unpredictability of the scenarios rose, other rules outperformed it. It was also presented to exist an inverse relation between queue size and the physician idle time. Keywords: discrete event simulation, idle-time, queue management, appointment scheduling, health care.

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