Discrete Event Simulation Approach Research Articles

An integrated approach of discrete event simulation and a non-radial super efficiency data envelopment analysis for performance evaluation of an emergency department

An emergency department (ED) has been considered as one of the most congested department in a hospital. The congestion is typically contributed by long waiting time to get medical service, primarily caused by insufficient resource allocation or improper resource configurations. However, how various resource allocation configurations affect ED performance and how their efficiency can correctly be evaluated, using an integrated approach is rarely discussed. This paper thus integrates discrete event simulation (DES) and data envelopment analysis (DEA) to measure ED performance and evaluate the efficiency of potential resource allocation configurations for future performance improvement. For this, a DES model for an ED is first designed and developed. Its performance improvement is then tested using 35 potential resource allocation configurations, and their impacts on the performance are measured. To evaluate their efficiency and identify the optimal configuration, a mixed integer super efficiency of slacks-based measure data envelopment analysis (SE-SBM-DEA) approach dealing with undesirable outputs is proposed. The model utilizes resource allocation as inputs and simulation performance measures as outputs. All inputs were considered as integer, while the outputs were classified into desirable and undesirable in mixed integer-valued data. The desirable real outputs are the utilization of receptionists, nurses and doctors. The undesirable real outputs are the average of patient cycle time and time spent in queues, while the undesirable integer output is average number of patients in queues. The desirable integer output is average number of patients received treatment. The results obtained from the DEA approach show that 21 efficient resource configurations have the capability to increase their inputs, undesirable outputs and/or decrease desirable outputs simultaneously without affecting their efficiency status. The integrated approach helps decision makers manage their healthcare facilities by identifying the sources of inefficiency and (the maximum levels of inputs-undesirable outputs and minimum levels of desirable outputs) to improve and (retain) efficiency.

Assessment of expected production of a deep‐sea mining system: An integrated model‐based systems engineering and discrete event simulation approach

AbstractIn this paper, model‐based systems engineering (MBSE) and discrete event simulation (DES) are combined to assess the performance of an offshore production system at an early stage. Various systems engineering tools are applied to an industrial case concerning the retrieval of deep‐sea minerals, and a simulation engine is developed to calculate the annual production output. A mean production of 1 Million tonnes of ore per year is estimated for an operation in the Norwegian Sea using Monte Carlo simulation. Depending on the limiting design wave height of the marine operations, the estimated production output ranges from 280,000 tonnes to 1.8 Million tonnes per year. The constrained parameter of the production system is particularly the wave height operational limit of the ship‐to‐ship transfer operation. We present the learning outcome from applying MBSE and DES to this case and discuss important aspects for improved performance.

A simulation model for predicting hospital occupancy for Covid-19 using archetype analysis

COVID-19 pandemic has sent millions of people to hospitals worldwide, exhausting on many occasions the capacity of healthcare systems to provide care patients required to survive. Although several epidemiological research works have contributed a variety of models and approaches to anticipate the pandemic spread, very few have tried to translate the output of these models into hospital service requirements, particularly in terms of bed occupancy, a key question for hospital managers. This paper proposes a tool for predicting the current and future occupancy associated with COVID-19 patients of a hospital to help managers make informed decisions to maximize the availability of hospitalization and intensive care unit (ICU) beds and ensure adequate access to services for confirmed COVID-19 patients. The proposed tool uses a discrete event simulation approach that uses archetypes (i.e., empirical models of trajectories) extracted from empirical analysis of actual patient trajectories. Archetypes can be fitted to trajectories observed in different regions or to the particularities of current and forthcoming variants using a rather small amount of data. Numerical experiments on realistic instances demonstrate the accuracy of the tool’s predictions and illustrate how it can support managers in their daily decisions concerning the system’s capacity and ensure patients the access the resources they require.

Warehouse Performance Improvement During Big Event using Discrete Event Simulation approach : A Case Study of Food and Beverages Company in Shah Alam

The purpose of this study is to see how customer demand changes when Malaysian e-commerce hosts a major event affect the warehouse operations. This is due to the fact that, when compared to non-major events, the pricing are very reasonable. As a result, when the major events happen, e-commerce especially the warehouse operations will face significant challenges in managing customer orders. Long lines can be found in the picking and packing sections. Orders will then be shipped later than anticipated. In this study, Company X is one of the e-commerce companies affected by this issue. Discrete Event Simulation (DES) was used as the method in measuring the warehouse performance under study. By introducing several scenarios that are appropriate for company X, the company's warehouse performance is found to be more efficient in terms of reducing process queuing time and resource utilization.

Optimising Maintenance Workflows in Healthcare Facilities: A Multi-Scenario Discrete Event Simulation and Simulation Annealing Approach

Healthcare systems in low-resource settings need effective methods for managing their scant resources, especially people and equipment. Digital technologies may provide means for circumventing the constraints hindering low-income economies from improving their healthcare services. Although analytical and simulation techniques, such as queuing theory and discrete event simulation, have already been successfully applied in addressing various optimisation problems across different operational contexts, the literature reveals that their application in optimisation of healthcare maintenance systems remains relatively unexplored. This study considers the problem of maintenance workflow optimisation with respect to labour, equipment availability and cost. The study aims to provide objective means for forecasting resource demand, given a set of task requests with varying priorities and queue characteristics that flow from multiple queues, and in parallel, into the same maintenance process for resolution. The paper presents how discrete event simulation is adopted in combination with simulated annealing to develop a decision-support tool that helps healthcare asset managers leverage operational performance data to project future asset-performance trends objectively, and thereby determine appropriate interventions for optimal performance. The study demonstrates that healthcare facilities can achieve efficiency in a cost-effective manner through tool-generated maintenance strategies, and that any future changes can be expeditiously re-evaluated and addressed.

Environment and economic analysis of reverse supply chain scenarios for remanufacturing using discrete-event simulation approach.

The study covers the concepts involved in reverse supply chain modeling using the case of a manufacturing company. The purpose of this study is to build a sustainable reverse supply chain model for resource conservation through remanufacturing of stator shafts by using a discrete-event simulation approach. The simulation studies in the reverse supply chain have taken up cases of either plastic or electronic waste remanufacturing, while very limited studies deal with simulation of sustainable reverse supply chains using a manufacturing industry case study from international customers. In this study, reverse supply chain using simulation study in manufacturing sector is carried out using Arena Rockwell simulation software. The simulation model is built using discrete-event simulation for returns from customers of two developed countries, i.e., Germany and the USA to Chennai, India. The study emphasizes full container load and less than container load modes of shipment scenarios and multiple return cases. The comparative analysis suggests that the value-added and non-value-added time of the reverse supply chain is slightly greater in the less container load scenario. The wait time per entity in remanufacturing processes similar for both shipment scenarios varies significantly based on return cases. The cost and carbon emission associated with transportation, in the reverse supply chain inclusive of social carbon cost, have also been estimated. Therefore, the study proposes a possible sustainable reverse supply chain framework that could be adopted by different manufacturing industries and yield opportunities for performance improvement.

Quantifying the Operational Benefits of Dry Port Integrated Cooperation in Port Clusters: A Microsimulation Study

As marine cargo traffic continues to grow, ports are experiencing increasing problems with congestion. To address this issue without requiring significant capital investment, neighboring ports can share their capacity to meet the rising demand for cargo throughput. While there are many planning level studies on inter-port cooperation, there is a scarcity of operational-level studies, and there is currently no available dry port integrated cooperation scheme for port clusters that utilizes a microsimulation approach. This study aims to contribute to the existing literature by proposing a conceptual port integration scheme that includes a dry port for improved coordination between ports in clusters. The discrete event simulation (DES) approach was used to construct three representative microsimulation models with dry port integration considering vessel transfer policies and no-cooperation scenario. The outputs of the models were evaluated using performance metrics (vessel delays, storage capacities, and the number of serviced vessels) using t-test statistics. The results show that the cooperation scheme with the vessel transfer policy and the strategic management of vessel transfer can significantly reduce the vessel operation delay by over 39% for the no-cooperation scenario with an integrated dry port and this value is further improved to 62% if a simulation-based port selection module (PSM) is used for vessel transfer policy. Additionally, the mean number of containers of the average of two port storages decreased by 40% and further decreased by 69% with the PSM. In terms of decision-making performance for vessel transfer decisions with varying quay lengths, PSM was determined to be superior to the vessel transfer policy considering the number of vessels in port queues. The proposed conceptual port integration model and approach can assist decision-makers in evaluating the effectiveness of different cooperation schemes and vessel transfer policies for adjacent ports in port clusters.

Economic and environmental analysis of biomass pellet supply chain using simulation-based approach

The pellet supply chain (PSC) is arguably crucial in supplanting fossil energy sources. Despite being the world's second-largest exporter of biomass pellets, the operation of PSC components in Vietnam is still fragmented and lacks economic and environmental efficiency. Changes in Bill of Material (BOM) help achieve these objectives. Discrete event simulation (DES) is particularly adapted to assist business owners in identifying BOM variation and its impacts on their real-life PSCs. Exploiting the advantages of the DES approach, this paper presents an evaluation model for the PSC, including procurement, production, transportation, and delivery modules. Simulation results yield a profit of USD 15,426,661, equivalent to roughly 20% of the revenue. The total amounts of carbon dioxide (CO2) emitted during production and transportation are 7,680.6 and 28,627.0 tons, respectively. The model is further used to assess the volatility of financial indicators and CO2 emission from changes in the raw materials for production. The findings suggest that maintaining the small-scale BOM level should be a solution for improving the economic and environmental efficiency of PSC components in Vietnam.

A quantitative analysis of inaccuracy inventory reducing in multi-period mode: Comparison between RFID and inventory counting

Inventory management decisions are one of the essential factors influencing the profitability of each supply chain member. However, in the real world and due to errors, the physical inventory and the inventory on the information system are frequently not matched, impacting the decision-making regarding inventory control. As a result, managers are constantly looking for ways to eliminate or reduce inventory errors. This study examines a retailer’s inventory control problem with transaction errors over time. For this purpose, a single-item multi-period model that adheres to a periodic review policy will be used. Therefore, the impact of two solutions, inventory counting and using RFID technology, on eliminating or reducing errors is assessed. In the section on inventory counting, unlike most papers that consider a counting cycle for inventory, it will be determined at the end of which period the inventory counting should be performed by acquiring the profit functions and their parameters. Also, when using RFID technology, it may occasionally fail to track the products, so the profit function is acquired with this error rate in mind. Moreover, it is determined when the inventory on the information system should be reset to eliminate errors accumulated over time. Furthermore, because these solutions each have costs, the discrete-event simulation approach calculates their profitability. Also, the profit changing of these solutions will be analyzed about various parameters.

Supply Chain Resilience Analysis Considering Disruption in the Natural Stone Industry Using a Discrete-Event Simulation Approach

برای دستیابی به مزیت رقابتی در شرایط عدم‌­اطمینان که در آن تغییر ضروری است، یکی از چالش‌های بزرگ سازمان‌ها کاهش ریسک از طریق ایجاد زنجیره‌های تأمین تاب‌آور است. تاب‌آوری در زنجیره ‌تأمین به توانایی زنجیره ‌تأمین برای مقابله با اختلال اشاره دارد که اختلال یک رویداد غیرقابل‌پیش‌بینی بوده و دارای منابع داخلی و خارجی مختلفی ازجمله بلایای طبیعی و ریسک‌های عملیاتی است. در پژوهش حاضر به شبیه‌سازی اختلال توسط نرم‌افزار ارنا در یک زنجیره‌ تأمین سنگ ساختمانی در «کارخانه سنگبری آسمان» پرداخته شده است. مدت‌زمان اجرای شبیه‌سازی یک سال و تعداد دفعات اجرای مدل شبیه‌سازی 100 بار در نظر گرفته شد. پس از اعتبارسنجی مدل از طریق مقایسه نتایج حاصل از شبیه‌سازی با اطلاعات واقعی کارخانه با محاسبه میانگین قدر مطلق خطا و تأیید اعتبار مدل، سناریوهای مختلف برای مدیریت اختلال و نشان‌دادن تاب‌آوری سیستم ایجاد و آزمایش شدند؛ سپس بر اساس معیار‌های نرخ پاسخگویی به تقاضای مشتریان، هزینه تقاضای پس‌افت و هزینه کل، عملکرد هر یک از سناریوها ارزیابی و درنهایت سناریو افزونگی برای اجرا در دنیای واقعی انتخاب شد؛ نتایج نشان داد که برای تاب‌آور­کردن سیستم، یک خط تولید پشتیبان در کارخانه راه‌­اندازی شود.

Leveraging discrete event simulation modeling to evaluate design and process improvements of an emergency department

This study exemplifies the practical application of the Discrete Event Simulation (DES) approach for evaluating the effectiveness of suggested processes and design modifications in improving the existing bottlenecks of an Emergency Department. EDs are under escalating pressure to deliver efficient care while handling considerable challenges, such as overcrowding, delays, length of stay, safety risks, or staffing. Many ED appointments are non-urgent and can be treated in an alternative outpatient setting. Suitable demand-capacity matching and adjusted admission protocols reduce ED patients' Length of Stay (LOS) and improve boarding times. Alternatively, new design suggestions include applying results-pending areas where lower acuity patients wait for their pending lab or imaging results. In this study, DES assesses underlying conditions and existing bottlenecks in an existing ED. The current ED flow involved a "pull-until-full" for exam room boarding and bedside registration after triage fulfillment. Nonetheless, the ED experienced boarding delays for patients waiting to be admitted into the hospital. This study explored two scenarios in DES as potential alternatives for reducing LOS: the implication of a "rapid-admit" protocol and a "results-pending" area. Findings showed that the Rapid-Admit process reduced the admitted patient's LOS by 16%. On average, the results-pending implication reduced the admit LOS by an average of 32% across all ESI levels. These findings suggest the importance of process, staffing, and spatial modifications to achieve ED operational improvements. DES enabled a data-driven approach to evaluate bottlenecks, enhance architect-owner communication, and optimize the system for future design and process improvement alternatives.

Modeling Real-time operations of Metro-based urban underground logistics system network: A discrete event simulation approach

Fast-growing logistics demand aggravates traffic congestion while posing great pressure on the urban ecology. A prospective solution is to split extensive goods movement from roads to underground, especially the metro systems. This paper proposes a simulation-based approach for supporting the operational decision-making of the metro-based urban underground logistics system (M−ULS). Based on a holistic concept of M−ULS network archetypes, two integration schemes of passengers and freight transport in metro network (i.e., collinear-detached metro and the collinear-trailer metro) are explicated. Next, mechanisms of metro freight service assignment, standardized packing, timetable coordination, and rolling stock circulation are proposed and formulated considering multiple criteria and travel patterns. A data-driven discrete-event simulation model with user interface is developed to acquire the real-time operating states of M−ULS in 36 tested scenarios. Experiments conducted on the Nanjing Metro case show that the proposed method can effectively capture the dynamic performance and bottlenecks of network operations in different operating periods and environments. The two considered system schemes show respective advantages in terms of freight demand backlog, capacity, traffic flow control, and efficiency, both of which have good compatibility with metro passenger services. The value of this paper is to provide a quantifiable design framework and assessment paradigm for M−ULS operations. It also offers new insights for solving “big-city diseases” and the potential innovations of urban underground space and metro systems.

A discrete event simulation approach for mine development planning at Codelco's New Mine Level

The new caving megaprojects that are planned to go into production in the next decade have scheduled horizontal developments at very high rates, which are difficult to achieve. Research has been conducted that seeks to model the construction times for underground developments to determine the feasibility of achieving the planned rates. However, these previous attempts do not consider all the operational aspects that make up the mine development cycle. Here, we present a discrete event simulation (DES) model that individualizes each unit operation of the development cycle to determine the construction rates that new projects will be able to attain. The developed model was applied to the New Mine Level (NML) of the El Teniente Division (DET). The results indicate that it would be impractical to achieve the advance rates scheduled in the original plans if the unit operations of the mine continue to be executed using the status quo. The metres developed after six years in the sections analysed can be significantly improved by changing the maintenance strategy for the equipment (457 metres increase), orepass availability (194 metres increase), and the initial planning sequence (1 598 metres increase). It is recommended that the mine implements a flexible maintenance strategy, defines a strategy to ensure and increase orepass availability to contractors, and makes use of current simulation tools for a more robust development sequence planning.

A simulation model for assessing the potential of remanufacturing electric vehicle batteries as spare parts

Remanufacturing is a key element of circular economy solutions as it aims at increasing the service lifetime of entire products or specific components, which may reduce the demand for new, resource-consuming devices. To assess the potential of disassembling and subsequent remanufacturing of EV batteries , we present a discrete event simulation approach. This approach depicts the life cycle of batteries and EVs separately, which allows capturing the demand for spare batteries and the potential contribution of remanufacturing batteries to cover this demand. By running various scenarios taking the German EV market as an example, the importance of providing cost-effective spare batteries through remanufacturing is underlined. As a baseline, a linear case is examined, where remanufacturing is not an option. Additionally, we built scenarios where remanufactured batteries are used as spare parts for older vehicles. Another major variation is introduced by different average battery lifetimes (10, 15, and 20 years), while the average vehicle lifetime is 15 years in all cases. The results show that remanufactured spare batteries could decrease the demand for new batteries compared to the linear base case. When battery lifetimes are lower than those of vehicles, new battery demand could be reduced by 6–7%, given our assumptions. In future scenarios where expected battery lifetimes might exceed vehicle lifetimes, up to 2% savings in new batteries could still be possible. Therefore, remanufacturing could be a viable option for improving the sustainability of electric mobility, and (re)manufacturers should consider intensifying their engagement in designing remanufacturable batteries, in research on remanufacturing technologies, and in investing in remanufacturing infrastructure. • Supply of and demand for remanufactured batteries are determined simultaneously. • The model considers incompatibilities between vehicles and remanufactured batteries. • Remanufacturing EV batteries could lower the demand for new batteries. • Frequent changes in battery technology could limit the remanufacturing potential.

A Trajectory Evaluation Platform for Urban Air Mobility (UAM)

Nowadays, there is an increase in the demand for optimized services in urban environments. However, ground transportation in big urban centers has been facing challenges for many years (e.g., resilience and congestion) and new paradigms have been proposed, such as the Urban Air Mobility (UAM) concept. UAM aims to enhance the urban transportation system using manned and unmanned aerial vehicles (i.e., Electric Vertical Takeoff and Landing - eVTOL - vehicles). Although UAM offers many benefits (e.g., cost reduction and increase in transportation capacity), many challenges need to be faced to enable safe and efficient operations. Furthermore, trajectory planning is challenging in the National Airspace System (NAS) and UAM operations due to several factors. Finally, new initiatives concerning UAM trajectory planning can be accelerated with the support of an automatic what-if platform capable of evaluating trajectories feasibility and efficiency. This research aims to propose a simulation platform for enabling trajectory evaluation in UAM operations. This platform, named Trajectory-Based Urban Air Mobility Simulator (TUS), focuses on simulating trajectories in the urban aerial environment. TUS enables users to test new UAM algorithms (e.g., flow management strategies, real-time evaluation of maneuvers effectiveness, airspace configurations) and simulate both manned and unmanned vehicles. Furthermore, TUS operation relies on a set of inputs and evaluates the trajectories generated from efficiency and safety perspectives. This process is performed using a Discrete Event Simulation (DES) approach. The experiments performed showed that TUS can perform a realistic evaluation of UAM trajectories and can be effortlessly used to simulate hundreds of scenarios.

How We Can Reap the Full Benefit of Teleconsultations: Economic Evaluation Combined With a Performance Evaluation Through a Discrete-Event Simulation.

BackgroundIn recent years, the rapid development of information and communications technology enabled by innovations in videoconferencing solutions and the emergence of connected medical devices has contributed to expanding the scope of application and expediting the development of telemedicine.ObjectiveThis study evaluates the use of teleconsultations (TCs) for specialist consultations at hospitals in terms of costs, resource consumption, and patient travel time. The key feature of our evaluation framework is the combination of an economic evaluation through a cost analysis and a performance evaluation through a discrete-event simulation (DES) approach.MethodsThree data sets were used to obtain detailed information on the characteristics of patients, characteristics of patients’ residential locations, and usage of telehealth stations. A total of 532 patients who received at least one TC and 18,559 patients who received solely physical consultations (CSs) were included in the initial sample. The TC patients were recruited during a 7-month period (ie, 2020 data) versus 19 months for the CS patients (ie, 2019 and 2020 data). A propensity score matching procedure was applied in the economic evaluation. To identify the best scenarios for reaping the full benefits of TCs, various scenarios depicting different population types and deployment strategies were explored in the DES model. Associated break-even levels were calculated.ResultsThe results of the cost evaluation reveal a higher cost for the TC group, mainly induced by higher volumes of (tele)consultations per patient and the substantial initial investment required for TC equipment. On average, the total cost per patient over 298 days of follow-up was €356.37 (US $392) per TC patient and €305.18 (US $336) per CS patient. However, the incremental cost of TCs was not statistically significant: €356.37 – €305.18 = €51.19 or US $392 – US $336 = US $56 (95% CI –35.99 to 114.25; P=.18). Sensitivity analysis suggested heterogeneous economic profitability levels within subpopulations and based on the intensity of use of TC solutions. In fact, the DES model results show that TCs could be a cost-saving strategy in some cases, depending on population characteristics, the amortization speed of telehealth equipment, and the locations of telehealth stations.ConclusionsThe use of TCs has the potential to lead to a major organizational change in the health care system in the near future. Nevertheless, TC performance is strongly related to the context and deployment strategy involved.

Hybrid modelling and simulation of the effect of vaccination on the COVID-19 transmission

ABSTRACT COVID-19 is a rapidly changing pandemic that requires different mitigation strategies to maintain clinical preventive services, including vaccination. Countries around the world have started administering the authorised COVID-19 vaccines. However, the number of positive cases remains at high levels. This paper simulates the transmission of COVID-19 over time using a hybrid simulation model, consisting of agent-based and discrete event simulation approaches. The model allows simulating the spread of the virus under various parameters, such as hospital capacities and vaccination policy, to observe the effects of each parameter on the virus transmission. The model and results can provide insights on how the daily vaccination rates and available medical capacity affect the number of deaths and infections. The model can be used to determine the required medical resources and vaccine supplies over time not only for COVID-19 but also for future pandemics with similar characteristics.

A study on how to achieve flexibility in healthcare process: a simulation-based approach

PurposeThe paper aims to investigate the cardiology department’s operational system for improving flexibility by minimizing the patient waiting time and simultaneously maximizing the utilization of service capacity in an uncertain environment. This article also proposes a policy framework that suggests a pool of additional resources and inter-firm collaboration can boost healthcare service delivery excellence.Design/methodology/approachA discrete event simulation (DES) approach is followed for modeling patient flow and determining the service capacity to respond to demand variability and uncertainty. The model's outputs are used to minimize patient waiting time, maximize the utilization of the resources and match the service capacity with the patient demand.FindingsThis research has tested two hypotheses and proved that an increase in waiting time decimates the throughput rate, and additional resources deployment in bottleneck activity positively impacts the throughput rate. The simulated scenarios prescribe an enhanced service capacity with quality care and further contribute to operational performance in reduced waiting time and cost. The results indicate that flexibility reduces the patient waiting time and maximizes the throughput rate.Practical implicationsThe study guides the healthcare policymakers to develop flexible competence and facilitate service mechanisms that are adaptive and robust while operating under a volatile environment. The article contributes to the healthcare literature that conjoins flexibility through simulation and resource utilization.Originality/valueThis research is based on real-life primary data collected from healthcare providers. This study adds value to the healthcare systems to adopt strategic decisions to build flexibility through resource allocation, sharing and coordinated care.

Impact of Universal Suicide Risk Screening in a Pediatric Emergency Department: A Discrete Event Simulation Approach.

ObjectivesThe aim of this study was to use discrete event simulation (DES) to model the impact of two universal suicide risk screening scenarios (emergency department [ED] and hospital-wide) on mean length of stay (LOS), wait times, and overflow of our secure patient care unit for patients being evaluated for a behavioral health complaint (BHC) in the ED of a large, academic children’s hospital.MethodsWe developed a conceptual model of BHC patient flow through the ED, incorporating anticipated system changes with both universal suicide risk screening scenarios. Retrospective site-specific patient tracking data from 2017 were used to generate model parameters and validate model output metrics with a random 50/50 split for derivation and validation data.ResultsThe model predicted small increases (less than 1 hour) in LOS and wait times for our BHC patients in both universal screening scenarios. However, the days per year in which the ED experienced secure unit overflow increased (existing system: 52.9 days; 95% CI, 51.5–54.3 days; ED: 94.4 days; 95% CI, 92.6–96.2 days; and hospital-wide: 276.9 days; 95% CI, 274.8–279.0 days).ConclusionsThe DES model predicted that implementation of either universal suicide risk screening scenario would not severely impact LOS or wait times for BHC patients in our ED. However, universal screening would greatly stress our existing ED capacity to care for BHC patients in secure, dedicated patient areas by creating more overflow.

Performance improvement in cardiology department of a hospital by simulation

The healthcare industry plays a vital role in the life of humankind and in the economic development of a country. Healthcare services have to be provided to mankind as and when required, without time delay and compromise on quality. This research focuses on reduction of waiting time of patients as it is considered as one of the important parameters that governs the service quality and is considered to improve patient satisfaction. This was studied by performing a case study in cardiology outpatient department of a private hospital in South India. Cardiology was chosen as it is one of the most critical areas which demands immediate attention. The study follows a discrete event simulation approach for analysing the trajectory of patients in the cardiology department, determining various performance parameters, suggesting changes in the existing system and developing alternate models to compare the results with those of the existing model. Reducing waiting time permits physicians to address more number of patients in a given period which are evident from the results obtained from the developed models. Simulation results revealed that the four alternate systems proposed were effective than the existing system.