Modeling healthcare demand using a hybrid simulation approach

Mielczarek, Bożena; Zabawa, Jacek

doi:10.1109/wsc.2016.7822204

Cited by 15 publications

(5 citation statements)

References 30 publications

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“…The hybrid simulation has been applied in areas such as clinical medicine ( 70 ); spread of disease in conjunction with different interventions ( 71 ); healthcare technology assessment ( 72 ); and forecasting population growth for healthcare demand ( 73 ). Hybrid simulation studies have used SD for modeling population dynamic in relation to disease progression, DES for representing healthcare clinics, and ABM was used for modeling individuals with characteristics such as age, gender, and behavior (e.g., interaction between individuals).…”

Section: Related Workmentioning

confidence: 99%

Modeling disease progression and treatment pathways for depression jointly using agent based modeling and system dynamics

Brice

Harper

Gärtner

et al. 2023

Front. Public Health

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IntroductionDepression is a common mental health condition that affects millions of people worldwide. Care pathways for depression are complex and the demand across different parts of the healthcare system is often uncertain and not entirely understood. Clinical progression with depression can be equally complex and relates to whether or not a patient is seeking care, the care pathway they are on, and the ability for timely access to healthcare services. Considering both pathways and progression for depression are however rarely studied together in the literature.MethodsThis paper presents a hybrid simulation modeling framework that is uniquely able to capture both disease progression, using Agent Based Modeling, and related care pathways, using a System Dynamics. The two simulation paradigms within the framework are connected to run synchronously to investigate the impact of depression progression on healthcare services and, conversely, how any limitations in access to services may impact clinical progression. The use of the developed framework is illustrated by parametrising it with published clinical data and local service level data from Wales, UK.Results and discussionThe framework is able to quantify demand, service capacities and costs across all care pathways for a range of different scenarios. These include those for varying service coverage and provision, such as the cost-effectiveness of treating patients more quickly in community settings to reduce patient progression to more severe states of depression, and thus reducing the costs and utilization of more expensive specialist settings.

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Section: Related Workmentioning

confidence: 99%

Modeling disease progression and treatment pathways for depression jointly using agent based modeling and system dynamics

Brice

Harper

Gärtner

et al. 2023

Front. Public Health

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show abstract

“…That research work was focused on patient pathways within large healthcare systems and suggested when and how to implement hybrid solutions [32]. In [33], the hybrid approach has been used to generate cardiac ill population samples, thereby making hybrid models more and more important in healthcare; ref. [34] provided a step-by-step simulation tutorial in real-world healthcare settings, with particular concern in privacy and security.…”

Section: Related Literaturementioning

confidence: 99%

Lean ICU Layout Re-Design: A Simulation-Based Approach

et al. 2022

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Healthcare facilities require flexible layouts that can adapt quickly in the face of various disruptions. COVID-19 confirmed this need for both healthcare and manufacturing systems. Starting with the transfer of decision support systems from manufacturing, this paper generalizes layout re-design activities for complex systems by presenting a simulation framework. Through a real case study concerning the proliferation of nosocomial cross-infection in an intensive care unit (ICU), the model developed in systems dynamics, based on a zero order immediate logic, allows reproducing the evolution of the different agencies (e.g., physicians, nurses, ancillary workers, patients), as well as of the cyber-technical side of the ICU, in its general but also local aspects. The entire global workflow is theoretically founded on lean principles, with the goal of balancing the need for minimal patient throughput time and maximum efficiency by optimizing the resources used during the process. The proposed framework might be transferred to other wards with minimal adjustments; hence, it has the potential to represent the initial step for a modular depiction of an entire healthcare facility.

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“…The second model was constructed using ExtendSim 9 by Imagine That Inc. to simulate demographic changes of the WR region. The sub-population model uses the system dynamics (SD) method and an aging chain approach to forecast the demographic changes that will be observed within the WR population over next 20 years (Mielczarek, Zabawa 2016b). The age-gender cohort simulation is performed using the deterministic approach, and hence there is no need to repeat the simulation runs.…”

Section: Sub Modelsmentioning

confidence: 99%

Healthcare Demand Simulation Model

Mielczarek¹,

Zabawa²

2018

ECMS 2018 Proceedings Edited by Lars Nolle, Alexandra Burger, Christoph Tholen, Jens Werner, Jens Wellhausen

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The aim of this paper is to study the influence of demography on the demand for healthcare services. The research is carried on in Wrocław Region (WR), Poland. We apply the system dynamic method and aging chain approach to simulate the number of individuals belonging to the respective age-gender cohorts. We consider such demographic descriptive parameters as birth and death rates, life expectancy and migration factors. Then, the discrete event simulation model is used to predict the annual demand for emergency hospital care, as registered at the hospitals located in the WR. The historical data on hospital admissions are drawn from National Health Fund regional branch. The input parameters describing the population are calculated based on historical and forecasted rates of primary demographic parameters, retrieved from various databases and official projections published by the Polish Central Statistical Office (CSO). The simulation predicts that between 2011 and 2020 the WR population will grow by 4.5% and the population aged 60+ will increase by 16.2%. Over the same period the number of arriving patients, compared to 2011, will be higher by 1.52%. Furthermore, the noticeable differences will be observed in the number of arrivals between particular hospitals.

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Modeling healthcare demand using a hybrid simulation approach

Cited by 15 publications

References 30 publications

Modeling disease progression and treatment pathways for depression jointly using agent based modeling and system dynamics

Modeling disease progression and treatment pathways for depression jointly using agent based modeling and system dynamics

Lean ICU Layout Re-Design: A Simulation-Based Approach

Healthcare Demand Simulation Model

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