Agent-Based Modeling

McLean, Allen; McDonald, Wade; Goodridge, Donna; Nathaniel, Osgood

doi:10.1097/nnr.0000000000000390

Cited by 5 publications

(1 citation statement)

References 36 publications

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“…The model included a number of agents, each representing one individual susceptible to develop LBP; a preliminary sensitivity study revealed that 300,000 agents were sufficient to capture the behaviour of the population, and using more agents would have a minimal impact on the results. We used epidemiological data of the incidence of LBP and simulated its evolution using precise real-world time horizon with increments of one day [ 16 ]. At the beginning of the simulation, each agent was randomly assigned an age, so that the simulated population replicated the age distribution of the population of the United States of America [ 17 ].…”

Section: Methodsmentioning

confidence: 99%

Expected impact of lockdown measures due to COVID-19 on disabling conditions: a modelling study of chronic low back pain

2021

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Purpose The COVID-19 pandemic and the containment measures such as social distancing, mobility restrictions and quarantine have significantly impacted the delivery of healthcare services, with possible negative effects on low back pain patients. In this study, we used an innovative agent-based model to quantify the effects of COVID-19 on the prevalence and severity of low back pain in the general population. Methods Epidemiological data were used to simulate the low back pain evolution in a population of 300,000 agents. Reduced access to treatment due to the containment measures was simulated with a probabilistic approach, in which 500 random scenarios (differing in: length of the lockdown, probability of having access to treatment, time before the resumption of treatment, duration of the effects of the treatment after its interruption) were simulated. Results The lockdown may increase the mean pain score higher than 1/10 points for patients suffering from acute low back pain, up to 4–5/10 points for specific individuals. The lockdown also affected the length of pain episodes, possibly impacting chronicity and disability. All the variables describing the random scenarios had a relevant impact in determining both the increase of pain intensity in the population and the length of the effects of the lockdown. Conclusions “Optimal lockdown parameters” which minimize the impact on low back pain while preserving the effects on infection spread and mortality could not be identified. Policies favouring a prompt resumption of treatments after the lockdown may be effective in shortening the duration of its negative effects.

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Section: Methodsmentioning

confidence: 99%

Expected impact of lockdown measures due to COVID-19 on disabling conditions: a modelling study of chronic low back pain

2021

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Agent-Based Modeling Simulation of Nurse Medication Administration Errors

Berg

Sawhney

et al. 2020

CIN: Computers, Informatics, Nursing

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It has been 20 years since the National Academy of Medicine released its report, “To Err Is Human,” which shocked the healthcare community on the pervasiveness of medical error. While errors in medication administration are a significant contributor to medical error, research seeking to understand the complex systems nature and occurrence of medication administration error is limited. Computer modeling is increasingly being used in the healthcare industry to assess the impact of changes made to healthcare processes. The objective of the study is to evaluate the use of agent-based modeling, a type of computer modeling that allows the simulation of virtual individuals and their behavior, to simulate nurse performance in the medication administration process. The model explores the effect of Just-in-Time information, as an intervention, on the occurrence of medication error. The model demonstrated significant utility in understanding the interplay of the system elements of the nurse medication administration process. Therefore this approach, using systems-level computer simulation such as agent-based models, can help administrators understand the effects of changes to the medication administration process as they work to reduce errors and increase performance.

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Simulation Modeling as a Novel and Promising Strategy for Improving Success Rates With Research Funding Applications: A Constructive Thought Experiment

2020

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Writing a successful grant or other funding applications is a requirement for continued employment, promotion, and tenure among nursing faculty and researchers. Writing successful applications is a challenging task, with often uncertain results. The inability to secure funding not only threatens the ability of nurse researchers to conduct relevant health care research but may also negatively impact their career trajectories. Many individuals and organizations have offered advice for improving success with funding applications. While helpful, those recommendations are common knowledge and simply form the basis of any well-considered, well-formulated, and well-written application. For nurse researchers interested in taking advantage of innovative computational methods and leading-edge analytical techniques, we propose adding the results from computer-based simulation modeling experiments to funding applications. By first conducting a research study in a virtual space, nurse researchers can refine their study design, test various assumptions, conduct experiments, and better determine which elements, variables, and parameters are necessary to answer their research question. In short, simulation modeling is a learning tool, and the modeling process helps nurse researchers gain additional insights that can be applied in their real-world research and used to strengthen funding applications. Simulation modeling is well-suited for answering quantitative research questions. Still, the design of these models can benefit significantly from the addition of qualitative data and can be helpful when simulating the results of mixed methods studies. We believe this is a promising strategy for improving success rates with funding applications, especially among nurse researchers interested in contributing new knowledge supporting the paradigm shift in nursing resulting from advances in computational science and information technology.

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Agent-Based Modeling

Cited by 5 publications

References 36 publications

Expected impact of lockdown measures due to COVID-19 on disabling conditions: a modelling study of chronic low back pain

Expected impact of lockdown measures due to COVID-19 on disabling conditions: a modelling study of chronic low back pain

Agent-Based Modeling Simulation of Nurse Medication Administration Errors

Simulation Modeling as a Novel and Promising Strategy for Improving Success Rates With Research Funding Applications: A Constructive Thought Experiment

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