Dataset Information

The Diffusion of Discrete Event Simulation Approaches in Health Care Management in the Past Four Decades: A Comprehensive Review.

ABSTRACT: This study systematically examines the diffusion of the discrete event simulation (DES) approach in health services and health care management by examining relevant factors such as research areas, channels with the objective of promoting the application of DES in the health field. We examined 483 journal papers referencing this approach that were published in 230 journals during 1981 to 2014. The application of DES has extended from health service operational research evaluation to the assessment of interventions in diverse health arenas. The increase in the number of adopters (paper authors) of DES and the increase in number of related channels (journals publishing DES-related articles) are highly correlated, which suggests an increase of DES-related publications in health research. The same conclusion is reached, that is, an increased diffusion of DES in health research, when we focus on the temporal trends of the channels and adopters. The applications of DES in health research cover 22 major areas based on our categorization. The expansion in the health areas also suggests to a certain extent the rapid diffusion of DES in health research.

SUBMITTER: Liu S

PROVIDER: S-EPMC7278318 | biostudies-literature | 2020 Jan-Jun

REPOSITORIES: biostudies-literature

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The Diffusion of Discrete Event Simulation Approaches in Health Care Management in the Past Four Decades: A Comprehensive Review.

Liu Shiyong S Li Yan Y Triantis Konstantinos P KP Xue Hong H Wang Youfa Y

MDM policy & practice 20200101 1

This study systematically examines the diffusion of the discrete event simulation (DES) approach in health services and health care management by examining relevant factors such as research areas, channels with the objective of promoting the application of DES in the health field. We examined 483 journal papers referencing this approach that were published in 230 journals during 1981 to 2014. The application of DES has extended from health service operational research evaluation to the assessmen ...[more]

PMID: 32551365

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Project description:BackgroundRapid growth of the integration of technology and psychotherapeutic interventions has been noted, but no clear quantification of this growth has been done.AimsThis bibliometric analysis seeks to quantify the growth, trends, and applications of technology in psychotherapeutic interventions over the last 40 years.MethodsSearches were conducted in the Web of Science (WOS) database for all existing technology-psychotherapy-related publications from 1981 to October 2020. Search terms were refined using a systematic screening strategy, based upon Cochrane protocol, generating 52 technology terms. Analyses across 40 years and by decade from 1981 to 2020 were conducted.ResultsA total of 13,934 peer-reviewed articles were identified. Yearly publication rate has increased from one in 1981 to 1902 by October 2020. The growth rate of publications across decades consistently tripled in size (762.50% from the 1980s to 1990s, 539.71% from the 1990s to 2000s, and 337.24% from the 2000s to 2010s). The author, country, journal, and institution with the most publications were Andersson, G., USA, Journal of Medical Internet Research, and Karolinska Institute, respectively. The most frequent technology search term across all four decades was "internet*." The trends in percentages of peer-reviewed publications within each decade showed: 1) a declining trend for the term "computer," 2) an upward trend for the combined terms, "internet," "online," and "web," 3) and a steady but smaller proportion of publications for other terms ("cell phone," "phone/telephone," "technology," "video," "virtual reality or VR," "apps," "digital," "machine learning," "electronic," "robo," and "telehealth").DiscussionThe rapid growth and trends identified in technology and psychotherapy publications can inform related policies addressing the role of technology in mental health. Moreover, pattern analyses may provide direction for a standard nomenclature to address terminology usage inconsistencies across the field.

Project description:It is recognized that the study of the disaster medical response (DMR) is a relatively new field. To date, there is no evidence-based literature that clearly defines the best medical response principles, concepts, structures and processes in a disaster setting. Much of what is known about the DMR results from descriptive studies and expert opinion. No experimental studies regarding the effects of DMR interventions on the health outcomes of disaster survivors have been carried out. Traditional analytic methods cannot fully capture the flow of disaster victims through a complex disaster medical response system (DMRS). Computer modelling and simulation enable to study and test operational assumptions in a virtual but controlled experimental environment. The SIMEDIS (Simulation for the assessment and optimization of medical disaster management) simulation model consists of 3 interacting components: the victim creation model, the victim monitoring model where the health state of each victim is monitored and adapted to the evolving clinical conditions of the victims, and the medical response model, where the victims interact with the environment and the resources at the disposal of the healthcare responders. Since the main aim of the DMR is to minimize as much as possible the mortality and morbidity of the survivors, we designed a victim-centred model in which the casualties pass through the different components and processes of a DMRS. The specificity of the SIMEDIS simulation model is the fact that the victim entities evolve in parallel through both the victim monitoring model and the medical response model. The interaction between both models is ensured through a time or medical intervention trigger. At each service point, a triage is performed together with a decision on the disposition of the victims regarding treatment and/or evacuation based on a priority code assigned to the victim and on the availability of resources at the service point. The aim of the case study is to implement the SIMEDIS model to the DMRS of an international airport and to test the medical response plan to an airplane crash simulation at the airport. In order to identify good response options, the model then was used to study the effect of a number of interventional factors on the performance of the DMRS. Our study reflects the potential of SIMEDIS to model complex systems, to test different aspects of DMR, and to be used as a tool in experimental research that might make a substantial contribution to provide the evidence base for the effectiveness and efficiency of disaster medical management.

Project description:ObjectivesThis feasibility study aimed to model in silico the current healthcare system for patients triaged to a primary care disposition following a call to National Health Service (NHS) 111 and determine the effect of reconfiguring the healthcare system to ensure a timely primary care service contact.DesignDiscrete event simulation.SettingSingle English NHS 111 call centre in Yorkshire.ParticipantsCallers registered with a Bradford general practitioner who contacted the NHS 111 service in 2021 and were triaged to a primary care disposition.Primary and secondary outcome measuresFace validity of conceptual model. Comparison between real and simulated data for quarterly counts (and 95% CIs) for patient contact with emergency ambulance (999), 111, and primary and secondary care services. Mean difference and 95% CIs in healthcare system usage between simulations and difference in mean proportion of avoidable admissions for callers who presented to an emergency department (ED).ResultsThe simulation of the current system estimated that there would be 39 283 (95% CI 39 237 to 39 328) primary care contacts, 2042 (95% CI 2032 to 2051) 999 calls and 1120 (95% CI 1114 to 1127) avoidable ED attendances. Modifying the model to ensure a timely primary care response resulted in a mean percentage increase of 196.1% (95% CI 192.2% to 199.9%) in primary care contacts, and a mean percentage decrease of 78.0% (95% CI 69.8% to 86.2%) in 999 calls and 88.1% (95% CI 81.7% to 94.5%) in ED attendances. Avoidable ED attendances reduced by a mean of -26 (95% CI -35 to -17).ConclusionIn this simulated study, ensuring timely contact with a primary care service would lead to a significant reduction in 999 and 111 calls, and ED attendances (although not avoidable ED attendance). However, this is likely to be impractical given the need to almost double current primary care service provision. Further economic and qualitative research is needed to determine whether this intervention would be cost-effective and acceptable to both patients and primary care clinicians.

Dataset Information

The Diffusion of Discrete Event Simulation Approaches in Health Care Management in the Past Four Decades: A Comprehensive Review.

Publications

The Diffusion of Discrete Event Simulation Approaches in Health Care Management in the Past Four Decades: A Comprehensive Review.

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