Geographic Service Delivery for Endovascular Clot Retrieval: Using Discrete Event Simulation to Optimize Resources

Endovascular clot retrieval is the standard of care for acute ischemic stroke caused by large vessel occlusion. However, access to mechanical thrombectomy remains limited in rural and regional areas, where patients often require transfer to urban centres. These delays are directly associated with poorer clinical outcomes. To address this disparity, a mechanical thrombectomy service was established at a regional tertiary hospital in North Queensland, Australia. This study aims to evaluate the safety and clinical outcomes of mechanical thrombectomy in a regional setting. A retrospective analysis was conducted on all consecutive patients who underwent mechanical thrombectomy at Townsville University Hospital (TUH), Queensland, Australia, between March 2022 and February 2024. Patients were categorized into two groups-local (TUH) and interhospital transfer-based on their initial presentation. Clinical outcomes, procedural success, and complications were assessed. A total of 120 patients (mean age: 71 years; 51 % male) underwent mechanical thrombectomy. Of these, 48 (40 %) presented locally, while 72 (60 %) were interhospital transfers. A good functional outcome (mRS 0-2 at 90 days) was achieved in 56 patients (47 %). Procedural success (mTICI score 2b-3) was observed in 106 patients (88 %), while 14 patients (12 %) experienced procedure-related complications. The establishment of a mechanical thrombectomy service at TUH has significantly improved access to stroke intervention for regional and rural populations in North Queensland. Our early experience demonstrates clinical outcomes comparable to those reported in large multicentre thrombectomy trials, confirming the feasibility and safety of delivering this service in a regional setting.

Endovascular clot retrieval (ECR) is the standard of care for acute ischaemic stroke due to large vessel occlusion. However, isolated occlusion of the M2 segment of the middle cerebral artery (MCA) was underrepresented in the landmark trials. Given the potential treatment benefit associated with M2 MCA occlusions, we aimed to evaluate the outcome of patients undergoing ECR for M2 occlusion. We conducted a systematic review and meta-analysis of the available literature that included patients with M2 MCA occlusions who underwent ECR. Successful reperfusion was defined as a treatment in cerebral ischaemia score of 2b-3. Good outcome was defined as a modified Rankin Scale score ≤ 2. We also analysed complications such as post-procedure symptomatic intracranial haemorrhage and mortality at 3 months. Fifteen studies including 1105 patients with isolated M2 occlusions were analysed. Successful reperfusion occurred in 75.4% (95% confidence interval (CI) 67.7-84.1%) of patients; good outcome was observed in 58.3% (95% CI 51.7-63.8% of patients. The rate of symptomatic intracranial haemorrhage was 5.1% (95% CI 4.2-8.3%), and 3-month mortality rate was 12.2% (95% CI 10.4-16.3%). The outcomes of ECR treatment of M2 occlusions are favourable, with good safety profile. Comparison to medical management from large registries or randomised controlled trials is warranted.

Modeling and analyzing a physician clinic environment using discrete-event (visual) simulation

IntroductionAlthough most of the stroke centers reported a remarkable decline in stroke care during the coronavirus disease 2019 (COVID-19) pandemic, data from Central Europe are limited.ObjectivesWe aimed to assess the...

MO3 COMPARING METHODS OF DATA SYNTHESIS: UPDATING PARAMETERS OF AN EXISTING PROBABILISTIC COST-EFFECTIVENESS MODEL

MO1 ADVANTAGES AND DISADVANTAGES OF MARKOV MODELS VERSUS DISCRETE EVENT MODELS FOR SIMULATING PATIENT FLOWS

A multicenter randomized clinical trial of endovascular treatment for acute ischemic stroke caused by proximal arterial occlusion in the anterior circulation.

One of the basic components of Industry 4.0 is the design of a flexible manufacturing system (FMS), which involves the choice of parameters to optimize its performance. Discrete event simulation (DES) models allow the user to understand the operation of dynamic and stochastic system performance and to support FMS diagnostics and design. In combination with DES models, optimization methods are often used to search for the optimal designs, which, above all, involve more than one objective function to be optimized simultaneously. These methods are called the multi-objective simulation–optimization (MOSO) method. Numerous MOSO methods have been developed in the literature, which spawned many proposed MOSO methods classifications. However, the performance of these methods is not guaranteed because there is an absence of comparative studies. Moreover, previous classifications have been focused on general MOSO methods and rarely related to the specific area of manufacturing design. For this reason, a new conceptual classification of MOSO used in FMS design is proposed. After that, four MOSO methods are selected, according to this classification, and compared through a detailed case study related to the FMS design problem. All of these methods studied are based on Design of Experiments (DoE). Two of them are metamodel-based approaches that integrate Goal Programming (GP) and Desirability Function (DF), respectively. The other two methods are not metamodel-based approaches, which integrate Gray Relational Analysis (GRA) and the VIKOR method, respectively. The comparative results show that the GP and VIKOR methods can result in better optimization than DF and GRA methods. Thus, the use of the simulation metamodel cannot prove its superiority in all situations.

Although Thrombolysis has been licensed in the UK since 2003, it is still administered only to a small percentage of eligible patients. We consider the impact of investing the impact of thrombolysis on important acute stroke services, and the effect on quality of life. The concept is illustrated using data from the Northern Ireland Stroke Service. Retrospective study. We first present results of survival analysis utilizing length of stay (LOS) for discharge destinations, based on data from the Belfast City Hospital (BCH). None of these patients actually received thrombolysis but from those who would have been eligible, we created two initial groups, the first representing a scenario where they received thrombolysis and the second comprising those who do not receive thrombolysis. On the basis of the survival analysis, we created several subgroups based on discharge destination. We then developed a discrete event simulation (DES) model, where each group is a patient pathway within the simulation. Coxian phase type distributions were used to model the group LOS. Various scenarios were explored focusing on cost-effectiveness across hospital, community and social services had thrombolysis been administered to these patients, and the possible improvement in quality of life, should the proportion of patients who are administered thrombolysis be increased. Our aim in simulating various scenarios for this historical group of patients is to assess what the cost-effectiveness of thrombolysis would have been under different scenarios; from this we can infer the likely cost-effectiveness of future policies. The cost of thrombolysis is offset by reduction in hospital, community rehabilitation and institutional care costs, with a corresponding improvement in quality of life. Our model suggests that provision of thrombolysis would produce moderate overall improvement to the service assuming current levels of funding.

Interventional neuroradiology (INR) has not yet received official certification as a surgical subspecialty in Ukraine. Consequently, there is uncertainty surrounding the availability of a neurosurgical internship and a structured INR training program to provide neuroendovascular procedures. In recent years, mechanical thrombectomy has become the standard of care for acute ischemic stroke caused by large vessel occlusion, as supported by evidence-based guidelines. This emphasizes the need for INR specialists, which far exceeds the current supply. Although stroke centres with interventional neuroradiological facilities have been established to address this shortage in Ukraine, they lack highly skilled staff. Following the relaxation of COVID-19 migration restrictions, the Ukrainian medical system faced new limitations due to ongoing wartime conditions. In such circumstances, international cooperation becomes crucial to ensuring the safe and effective implementation of new technologies into routine medical practice. We successfully integrated teleproctoring into our hands-on course and found it to be an effective and promising approach, especially considering the uncertainty of the future and the presence of wartime migration restrictions in Ukraine. Teleproctoring hands-on course has the potential to provide young specialists with experienced mentors and valuable initial experience and can serve as a valuable adjunct for the improvement of surgeons confidence.

A simulation optimization approach to investigate resource planning and coordination mechanisms in emergency systems

ObjectivesThis systematic review examines prehospital and in-hospital delays in acute stroke care in Indonesia.DesignSystematic review adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.Data sourcesWe conducted a thorough...

This paper provides an empirical study on the comparison of model building in Discrete-Event Simulation (DES) and System Dynamics (SD). Verbal Protocol Analysis (VPA) is used to study the model building process of ten expert modellers (5 SD and 5 DES). Participants are asked to build a simulation model based on a prison population case study and to think aloud while modelling. The generated verbal protocols are divided into 7 modelling topics: problem structuring, conceptual modelling, data inputs, model coding, validation & verification, results & experimentation and implementation and then analyzed. Our results suggest that all modellers switch between modelling topics, however DES modellers follow a more linear progression compared to SD modellers. DES modellers focus significantly more on model coding and verification & validation, whereas SD modellers on conceptual modelling. This quantitative analysis of the processes followed by expert modellers contributes towards the comparison of DES and SD modelling.

In manufacturing plants, part of assembly is often performed by human workers and therefore its performance largely depends on humans (or human performances) rather than machines. However, most studies on human centred assembly systems using the modelling simulation methods do not consider or incorporate the effects of human performance that may also impact the overall system performance of such as an assembly line. The prediction of human performance or behaviour in a manufacturing system evaluation is often overlooked by researchers or system designers partially due to a lack of proper versions of existing simulation tools that can incorporate human attributes into an established simulation model. This paper presents a study by incorporating human attributes of learning and ageing into a discrete event simulation (DES) model based on a human centred assembly system. The effects of worker performance due to aging and learning were investigated and identified through a literature review [1]. The simulation result demonstrates that the worker performance may approach his/her full capacity at the age of 38 years old and this may decrease by an average of 1% from 38 to 40 years old, and 6% at the age of 45 years old. After the age of 45 years old, the decline rate of worker performance may slow down as it can be offset by accumulating worker experience through learning.

This study employs a discrete event simulation (DES) model to understand the dynamic workload of remote truck operators managing partially-automated trucks. The DES model uses operator queues and event generators simulating automated truck events and leverages data from the California DMV’s disengagement database and driving simulation experiments. Disengagement data were partitioned into three groups by disengagement frequency: low, moderate, and high and separate arrival time distributions were developed for each group. Simulations from the model suggest that for companies with low disengagement rates, operator utilization will likely remain below minimal thresholds to prevent boredom. In contrast, companies with moderate or high disengagement rates both exceed operator utilization capacity and generate prolonged wait times as more trucks are controlled. These findings suggest that calibrating remote truck control to human capabilities will be challenging. A sensitivity analysis suggests that accurately estimating disengagement rates will be crucial for model accuracy and predictive performance.