Epidemiology and demand for healthcare: an agent-based simulation model

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A healthcare space planning simulation model for Accident and Emergency (A&E)

The National Health Service (NHS) in the United Kingdom provides a range service for its population including primary care and hospital services. The impact of the 2008 economic and financial crises prompted a tightening of public budgets including health. Over the next few years, and most likely beyond, the NHS is planning for unprecedented levels of efficiency saving in the order of £ billions. With little doubt, the NHS will need to review its way of working will need to do more with less. Simulation is an established technique with applications in many industries including healthcare. Potentially, there are huge opportunities for simulation use to make further inroads in the field of healthcare. Despite the potential, arguably, simulation has failed to make a significant impact in health. Some evidence has tended to suggest that within health there has been poor adaption along with poor linkage to real-world problems, as perceived by healthcare stakeholders. The aim of this thesis is to develop a model to help address real-world healthcare issues as recognised by healthcare stakeholders. In doing so, this thesis will focus on a couple of real-world problems, namely: What space is needed to meet service demand, when is it needed and what will it cost? What space do we have, how can it be used to meet service demand and at what cost? The developed simulation space demand model will demonstrate its value modelling dynamic systems over static models. The developed models will also show its value highlighting space demand issues by groups of patients, by time of day. Real, readily available data (arrival and length of stay, by patient group) would drive the model inputs, supporting ease of use and clarity for healthcare stakeholders. The model was modular by design to support rapid reconfiguration. Dynamically modelled space information allows service managers and Healthcare Planners to better manage and organise their space in a flexible way to meet service requirements. This work will also describe how space demand can linked with building notes to determine Schedules of Accommodation which can be used to cost floor space and consequent building or refurbishment costs. Furthermore, this information could be used to drive business plans and to develop operational cost pertaining to the floor area. This body of work debates using function-to-space ratios and attaching facilities management cost. Our findings suggest great variance in function-to-space ratios. Our findings also suggest that moving to median or lower quartile function-to-space ratios could potentially save hospitals £ millions in facilities management costs. This thesis will reflect on the level of modelling taking place in the healthcare industry by non-academic healthcare modellers, sometimes collectively known as Healthcare Planners, the Healthcare Planning role in space planning and their links with healthcare stakeholders. This reflection will also consider whether healthcare stakeholders perceive a great need for academic healthcare modelling, if they believe their modelling needs are met by Healthcare Planners. A central theme of this thesis is that academic modelling and Healthcare Planning have great synergy and that bringing together Healthcare Planners’ industry knowledge and stakeholder relationships with academic know-how, can make a significant contribution to the healthcare simulation modelling arena

Towards Leaner Healthcare Facility: Application of Simulation Modelling and Value Stream Mapping

Recently, the application of lean thinking in healthcare has grown significantly in response to rising demand caused by population growth, ageing and high expectations of service quality. However, insufficient justifications and lack of quantifiable evidence are the main obstacles to convince healthcare executives to adopt lean. Therefore, this paper presents a methodology that integrates lean tools with simulation to enhance the quality of patient care in healthcare facilities. This enables healthcare organisations to dedicate more time and effort to patient care without extra cost to the organisation or to the patient. Value stream mapping is used to identify value-added and non-value-added activities.. Then, a comprehensive simulation model is developed to account for the variability and complexity of healthcare processes and to assess the gains of proposed improvement strategies. An extensive analysis of results is provided and presented to managers to illustrate the potential benefits of adapting lean practices

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

Simulation of operational processes in hospital emergency units as lean healthcare tool

Recently, the Lean philosophy is gaining importance due to a competitive environment, which increases the need to reduce costs. Lean practices and tools have been applied to manufacturing, services, supply chain, startups and, the next frontier is healthcare. Most lean techniques can be easily adapted to health organizations. Therefore, this paper intends to summarize Lean practices and tools that are already being applied in health organizations. Among the numerous techniques and lean tools used, this research highlights the Simulation. Therefore, in order to understand the use of Simulation as a Lean Healthcare tool, this research aims to analyze, through the simulation technique, the operational dynamics of the service process of a fictitious hospital emergency unit. Initially a systematic review of the literature on the practices and tools of Lean Healthcare was carried out, in order to identify the main techniques practiced. The research highlighted Simulation as the sixth most cited tool in the literature. Subsequently, a simulation of a service model of an emergency unit was performed through the Arena software. As a main result, it can be highlighted that the attendants of the built model presented a degree of idleness, thus, they are able to atend a greater demand. As a last conclusion, it was verified that the emergency room is the process with longer service time and greater overload

The Potential Economic Impact of Avian Flu Pandemic on Taiwan

This study analyzes the potential consequences of an outbreak of avian influenza (H5N1) on Taiwan¡¦s macro economy and individual industries. Both the Input-Output (IO) Analysis Model and Computable General Equilibrium (CGE) Model are used to simulate the possible damage brought by lowering domestic consumption, export, and labor supply. The simulation results indicates that if the disease is confined within the poultry sector, then the impact on real GDP is around -0.1%~-0.4%. Once it becomes a human-to-human pandemic, the IO analysis suggests that the potential impacts on real GDP would be as much as -4.2%~-5.9% while labor demand would decrease 4.9%~6.4%. In the CGE analysis, which allows for resource mobility and substitutions through price adjustments, the real GDP and labor demand would contract 2.0%~2.4% and 2.2%~2.4%, respectively, and bringing down consumer prices by 3%. As for the individual sector, the outbreak will not only damage the poultry sector and its upstream and downstream industries, but also affect the service sectors including wholesale, retail, trade, air transportation, restaurants, as well as healthcare services. These results can be used to support public investment in animal disease control measures.Avian Flu Pandemic, Input-output Model, Computable General Equilibrium Model, Livestock Production/Industries,

Simulation-based Framework to Improve Patient Experience in an Emergency Department

The global economic crisis has a significant impact on healthcare resource provision worldwide. The management of limited healthcare resources is further challenged by the high level of uncertainty in demand, which can lead to unbalanced utilisation of the available resources and a potential deterioration of patient satisfaction in terms of longer waiting times and perceived reduced quality of services. Therefore, healthcare managers require timely and accurate tools to optimise resource utility in a complex and ever-changing patient care process. An interactive simulation-based decision support framework is presented in this paper for healthcare process improvement. Complexity and different levels of variability within the process are incorporated into the process modelling phase, followed by developing a simulation model to examine the impact of potential alternatives. As a performance management tool, balanced scorecard (BSC) is incorporated within the framework to support continual and sustainable improvement by using strategic-linked performance measures and actions. These actions are evaluated by the simulation model developed, whilst the trade-off between objectives, though somewhat conflicting, is analysed by a preference model. The preference model is designed in an interactive and iterative process considering decision makers preferences regarding the selected key performance indicators (KPIs). A detailed implementation of the framework is demonstrated on an emergency department (ED) of an adult teaching hospital in north Dublin, Ireland. The results show that the unblocking of ED outflows by in-patient bed management is more effective than increasing only the ED physical capacity or the ED workforce

A decision support system for demand and capacity modelling of an accident and emergency department

© 2019 Operational Research Society.Accident and emergency (A&E) departments in England have been struggling against severe capacity constraints. In addition, A&E demands have been increasing year on year. In this study, our aim was to develop a decision support system combining discrete event simulation and comparative forecasting techniques for the better management of the Princess Alexandra Hospital in England. We used the national hospital episodes statistics data-set including period April, 2009 – January, 2013. Two demand conditions are considered: the expected demand condition is based on A&E demands estimated by comparing forecasting methods, and the unexpected demand is based on the closure of a nearby A&E department due to budgeting constraints. We developed a discrete event simulation model to measure a number of key performance metrics. This paper presents a crucial study which will enable service managers and directors of hospitals to foresee their activities in future and form a strategic plan well in advance.Peer reviewe

Ambulatory Healthcare Utilization in the United States: A System Dynamics Approach

Ambulatory health care needs within the United States are served by a wide range of hospitals, clinics, and private practices. The Emergency Department (ED) functions as an important point of supply for ambulatory healthcare services. Growth in our aging populations as well as changes stemming from broader healthcare reform are expected to continue trend in congestion and increasing demand for ED services. While congestion is, in part, a manifestation of unmatched demand, the state of the alignment between the demand for, and supply of, emergency department services affects quality of care and profitability. The central focus of this research is to provide an explanation of the salient factors at play within the dynamic demand-supply tensions within which ambulatory care is provided within an Emergency Department. A System Dynamics (SO) simulation model is used to capture the complexities among the intricate balance and conditional effects at play within the demand-supply emergency department environment. Conceptual clarification of the forces driving the elements within the system , quantifying these elements, and empirically capturing the interaction among these elements provides actionable knowledge for operational and strategic decision-making

Estimating healthcare demand for an aging population: a flexible and robust bayesian joint model

In this paper, we analyse two frequently used measures of the demand for health care, namely hospital visits and out-of-pocket health care expenditure, which have been analysed separately in the existing literature. Given that these two measures of healthcare demand are highly likely to be closely correlated, we propose a framework to jointly model hospital visits and out-of-pocket medical expenditure. Furthermore, the joint framework allows for the presence of non-linear effects of covariates using splines to capture the effects of aging on healthcare demand. Sample heterogeneity is modelled robustly with the random effects following Dirichlet process priors with explicit cross-part correlation. The findings of our empirical analysis of the U.S. Health and Retirement Survey indicate that the demand for healthcare varies with age and gender and exhibits significant cross-part correlation that provides a rich understanding of how aging affects health care demand, which is of particular policy relevance in the context of an aging population