Using an Agent-based Simulation for Predicting the Effects of Patients Derivation Policies in Emergency Departments

AbstractThe increasing demand of urgent care, overcrowding of hospital emergency departments (ED) and limited economic resources are phenomena shared by health systems around the world. It is estimated that up to 50% of patients that are attended in ED have non complex conditions that could be resolved in ambulatory care services. The derivation of less complex cases from the ED to other health care devices seems an essential measure to allocate properly the demand of care service between the different care units. This paper presents the results of an experiment carried out with the objective of analyzing the effects on the ED (patients’ Length of Stay, the number of patients attended and the level of activity of ED Staff) of different derivation policies. The experiment has been done with data of the Hospital of Sabadell (a big hospital, one of the most important in Catalonia, Spain), making use of an Agent-Based model and simulation formed entirely of the rules governing the behaviour of the individual agents which populate the ED, and due to the great amount of data that should be computed, using High Performance Computing

Managing hospital visitor admission during Covid-19: A discrete-event simulation by the data of a German University Hospital

The Corona pandemic and the associated need for visitor restrictions have defined an entirely new management task in hospitals: The hospital visitor management. The admission process of hospital visitors and the implementation of associated infection-prevention strategies such as the delivery of face masks thereby pose major challenges. In this work, we evaluate both implemented and planned admission processes in a German University Hospital based on a discrete-event simulation model and provide distinct recommendations for hospital visitor management with special consideration of digitalization, antigen testing, waiting times, space and staff utilization. We find the extraordinary potential of digitalization with a reduction of visitor waiting and service times of up to 90 percent, the significant burden for personnel and room capacity, in terms of antigen testing, especially, and the need for visitor restrictions in terms of a maximum number of visitors per inpatient

Using discrete event simulation to improve the patient care process in the emergency department of a rural Kentucky hospital.

The patient care process of a rural Kentucky hospital is a complex process that must be flexible in order to deal with a large variety of patient needs and a fluctuating patient volume where all patients are unscheduled. A simulation model of an average month in the emergency department was built using the Arena Simulation package. Methods for creating a simulation using Arena are included in this work. Statistics were generated from a number of different sources to create an accurate representation of the model. The Hospital reporting shows a need to improve on two quality measures being tracked, the length of time a patient is in the emergency department from entry to completion of care, and the number of patients who leave without being seen by the physician (most often due to the length of their waiting room time prior to the initiation of care). Due to the complex nature of the emergency department and its impact by other departments of the Hospital as well as outside factors such as patient demand, the ability to quantify an expected gain from a change to the facility or to a process can be difficult to establish. A simulation model will allow for experiments on the system to be created and observed, thus enabling the Hospital to identify the best opportunities for improvement. Experiments included in this work show changes to the emergency department facility by adding an additional patient treatment bed, and changing a policy regarding transfer of a patient from the emergency department to inpatient care in the Hospital. Both experiments show improvement in quality measures, with reduced waiting room times, fewer patients who leave without being seen by the physician, and an overall reduction in the length of stay from entry to completion of care in the ED. In the creation of the simulation model, an objective was to develop a model that could be used to guide decision through its flexibility and statistical reliability. The model can be used to test a variety of physical or procedural changes to the emergency department, as well as to test to the impacts of increased patient volume

Developing service supply chains by using agent based simulation

The Master thesis present a novel approach to model a service supply chain with agent based simulation. Also, the case study of thesis is related to healthcare services and research problem includes facility location of healthcare centers in Vaasa region by considering the demand, resource units and service quality. Geographical information system is utilized for locating population, agent based simulation for patients and their illness status probability, and discrete event simulation for healthcare services modelling. Health centers are located on predefined sites based on managers’ preference, then each patient based on the distance to health centers, move to the nearest point for receiving the healthcare services. For evaluating cost and services condition, various key performance indicators have defined in the modelling such as Number of patient in queue, patients waiting time, resource utilization, and number of patients ratio yielded by different of inflow and outflow. Healthcare managers would be able to experiment different scenarios based on changing number of resource units or location of healthcare centers, and subsequently evaluate the results without necessity of implementation in real life.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

OPTIMAX 2014 - Radiation dose and image quality optimisation in medical imaging

Medical imaging is a powerful diagnostic tool. Consequently, the number of medical images taken has increased vastly over the past few decades. The most common medical imaging techniques use X-radiation as the primary investigative tool. The main limitation of using X-radiation is associated with the risk of developing cancers. Alongside this, technology has advanced and more centres now use CT scanners; these can incur significant radiation burdens compared with traditional X-ray imaging systems. The net effect is that the population radiation burden is rising steadily. Risk arising from X-radiation for diagnostic medical purposes needs minimising and one way to achieve this is through reducing radiation dose whilst optimising image quality. All ages are affected by risk from X-radiation however the increasing population age highlights the elderly as a new group that may require consideration. Of greatest concern are paediatric patients: firstly they are more sensitive to radiation; secondly their younger age means that the potential detriment to this group is greater. Containment of radiation exposure falls to a number of professionals within medical fields, from those who request imaging to those who produce the image. These staff are supported in their radiation protection role by engineers, physicists and technicians. It is important to realise that radiation protection is currently a major European focus of interest and minimum competence levels in radiation protection for radiographers have been defined through the integrated activities of the EU consortium called MEDRAPET. The outcomes of this project have been used by the European Federation of Radiographer Societies to describe the European Qualifications Framework levels for radiographers in radiation protection. Though variations exist between European countries radiographers and nuclear medicine technologists are normally the professional groups who are responsible for exposing screening populations and patients to X-radiation. As part of their training they learn fundamental principles of radiation protection and theoretical and practical approaches to dose minimisation. However dose minimisation is complex – it is not simply about reducing X-radiation without taking into account major contextual factors. These factors relate to the real world of clinical imaging and include the need to measure clinical image quality and lesion visibility when applying X-radiation dose reduction strategies. This requires the use of validated psychological and physics techniques to measure clinical image quality and lesion perceptibility

A distributed simulation methodology for large-scale hybrid modelling and simulation of emergency medical services

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonHealthcare systems are traditionally characterised by complexity and heterogeneity. With the continuous increase in size and shrinkage of available resources, the healthcare sector faces the challenge of delivering high quality services with fewer resources. Healthcare organisations cannot be seen in isolation since the services of one such affects the performance of other healthcare organisations. Efficient management and forward planning, not only locally but rather across the whole system, could support healthcare sector to overcome the challenges. An example of closely interwoven organisations within the healthcare sector is the emergency medical services (EMS). EMS operate in a region and usually consist of one ambulance service and the available accident and emergency (A&E) departments within the coverage area. EMS provide, mainly, pre-hospital treatment and transport to the appropriate A&E units. The life-critical nature of EMS demands continuous systems improvement practices. Modelling and Simulation (M&S) has been used to analyse either the ambulance services or the A&E departments. However, the size and complexity of EMS systems constitute the conventional M&S techniques inadequate to model the system as a whole. This research adopts the approach of distributed simulation to model all the EMS components as individual and composable simulations that are able to run as standalone simulation, as well as federates in a distributed simulation (DS) model. Moreover, the hybrid approach connects agent-based simulation (ABS) and discrete event simulation (DES) models in order to accommodate the heterogeneity of the EMS components. The proposed FIELDS Framework for Integrated EMS Large-scale Distributed Simulation supports the re-use of existing, heterogeneous models that can be linked with the High Level Architecture (HLA) protocol for distributed simulation in order to compose large-scale simulation models. Based on FIELDS, a prototype ABS-DES distributed simulation EMS model was developed based on the London EMS. Experiments were conducted with the model and the system was tested in terms of performance and scalability measures to assess the feasibility of the proposed approach. The yielded results indicate that it is feasible to develop hybrid DS models of EMS that enables holistic analysis of the system and support model re-use. The main contributions of this thesis is a distributed simulation methodology that derived along the process of conducting this project, the FIELDS framework for hybrid EMS distributed simulation studies that support re-use of existing simulation models, and a prototype distributed simulation model that can be potentially used as a tool for EMS analysis and improvement.MATCH Programm

Investigating efficiency in the emergency department at Groote Schuur Hospital

Includes bibliographical references (p. 92-93)