An agent-based model for quantitatively analyzing and predicting the complex behavior of emergency departments

Liu, Zhengchun; Rexachs, Dolores; Epelde, Francisco; Luque, Emilio

doi:10.1016/j.jocs.2017.05.015

Cited by 36 publications

(22 citation statements)

References 38 publications

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“…Games and participatory simulation are particularly useful for training at the tactical level because games help identify productive or counterproductive human actions. The strength of the agent-based method is the modeling and analysis of human behavior [ 33 , 41 ]. Healthcare logistics are largely characterized by non-rational operative decision making by medical personnel regarding needs of their patients.…”

Section: Discussionmentioning

confidence: 99%

A systematic literature review of simulation models for non-technical skill training in healthcare logistics

et al. 2018

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BackgroundResource allocation in patient care relies heavily on individual judgements of healthcare professionals. Such professionals perform coordinating functions by managing the timing and execution of a multitude of care processes for multiple patients. Based on advances in simulation, new technologies that could be used for establishing realistic representations have been developed. These simulations can be used to facilitate understanding of various situations, coordination training and education in logistics, decision-making processes, and design aspects of the healthcare system. However, no study in the literature has synthesized the types of simulations models available for non-technical skills training and coordination of care.MethodsA systematic literature review, following the PRISMA guidelines, was performed to identify simulation models that could be used for training individuals in operative logistical coordination that occurs on a daily basis. This article reviewed papers of simulation in healthcare logistics presented in the Web of Science Core Collections, ACM digital library, and JSTOR databases. We conducted a screening process to gather relevant papers as the knowledge foundation of our literature study. The screening process involved a query-based identification of papers and an assessment of relevance and quality.ResultsTwo hundred ninety-four papers met the inclusion criteria. The review showed that different types of simulation models can be used for constructing scenarios for addressing different types of problems, primarily for training and education sessions. The papers identified were classified according to their utilized paradigm and focus areas. (1) Discrete-event simulation in single-category and single-unit scenarios formed the most dominant approach to developing healthcare simulations and dominated all other categories by a large margin. (2) As we approached a systems perspective (cross-departmental and cross-institutional), discrete-event simulation became less popular and is complemented by system dynamics or hybrid modeling. (3) Agent-based simulations and participatory simulations have increased in absolute terms, but the share of these modeling techniques among all simulations in this field remains low.ConclusionsAn extensive study analyzing the literature on simulation in healthcare logistics indicates a growth in the number of examples demonstrating how simulation can be used in healthcare settings. Results show that the majority of studies create situations in which non-technical skills of managers, coordinators, and decision makers can be trained. However, more system-level and complex system-based approaches are limited and use methods other than discrete-event simulation.

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Section: Discussionmentioning

confidence: 99%

A systematic literature review of simulation models for non-technical skill training in healthcare logistics

et al. 2018

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“…For example, Ajmi et al [83] developed an agent-based dynamic optimization model for improving several performance indicators (LOS, remaining patient care load, and cumulative waiting time) in EDs. OR-based studies addressing long LOS are evidenced in Chan et al [91], Derni et al [87], Liu et al [95], and Oueida et al [86,96]. Apart from the aforementioned single techniques, less popular methods like critical pathways [88,89,97], pivot nursing [92], and process redesign [94] were also used by some practitioners and researchers to diminish the total burden produced by long ED-LOS.…”

Section: Papers Focusing On Reducing the Extended Losmentioning

confidence: 99%

Methodological Approaches to Support Process Improvement in Emergency Departments: A Systematic Review

Ortíz‐Barrios

Alfaro-Saiz

2020

IJERPH

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The most commonly used techniques for addressing each Emergency Department (ED) problem (overcrowding, prolonged waiting time, extended length of stay, excessive patient flow time, and high left-without-being-seen (LWBS) rates) were specified to provide healthcare managers and researchers with a useful framework for effectively solving these operational deficiencies. Finally, we identified the existing research tendencies and highlighted opportunities for future work. We implemented the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to undertake a review including scholarly articles published between April 1993 and October 2019. The selected papers were categorized considering the leading ED problems and publication year. Two hundred and three (203) papers distributed in 120 journals were found to meet the inclusion criteria. Furthermore, computer simulation and lean manufacturing were concluded to be the most prominent approaches for addressing the leading operational problems in EDs. In future interventions, ED administrators and researchers are widely advised to combine Operations Research (OR) methods, quality-based techniques, and data-driven approaches for upgrading the performance of EDs. On a different tack, more interventions are required for tackling overcrowding and high left-without-being-seen rates.

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“…Obtained Data Driven [5, 7-9, 11, 13, 32, 33, 37, 47-49, 54, 58, 62, 66, 70-72, 74-76, 80, 81, 83, 85-99, 104, 107, 108, 112, 120, 121, 124, 126, 127, 131, 133, 134, 138-140, 143, 144, 147-150, 153, 157, 160, 162, 167, 170, 172, 177-179, 183-185, 191, 192, 195, 197-206, 209-211] Collaboration [3,10,14,17,27,42,51,73,100,114,142,152,163] Both [12,20,35,40,56,101,103,129,136,146,154,166,171,186] Other [19,21,22,24,41,60,79,82,116,128,169] Table A6. Care level considered.…”

Section: Fundingmentioning

confidence: 99%

“…Scope Hospital [8, 21, 23, 27, 29-31, 36, 41, 51, 64, 67, 74-76, 79, 85, 108, 111, 114-117, 134, 142, 145-148, 152, 158, 160, 165, 166, 170, 177, 178, 184, 190, 202, 203, 209] Department [12,14,15,17,18,46,50,52,57,62,68,100,113,125,129,141,151,153,154,161,163,164,167,169,171,182,185,187,212] Clinical [1, 3, 5, 10, 11, 13, 16, 19, 20, 22, 32-35, 40, 42, 43, 45, 47, 53, 60, 70-73, 80-83, 87-99, 102, 107, 110, 112, 121, 124, 126-128, 133, 136, 139, 140, 149, 162, 179, 183, 186, 188, 191, 192, 195, 197-201, 204-206, 210, 211] Disease [4, 7, 9, 13, 24, 25, 37, 39, 43, 48, 49, 54-56, 58, 66, 86, 101-104, 118-120, 122, 128, 131, 138, 143, 144, 150, 157, 172, 196, 211] Table A5…”

Section: Fundingmentioning

confidence: 99%

Clinical pathway modelling: a literature review

2019

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Hospital information systems are increasingly used as part of decision support tools for planning at strategic, tactical and operational decision levels. Clinical pathways are an effective and efficient approach in standardising the progression of treatment, to support patient care and facilitate clinical decision making. This literature review proposes a taxonomy of problems related to clinical pathways and explores the intersection between Information Systems (IS), Operational Research (OR) and industrial engineering. A structured search identified 175 papers included in the taxonomy and analysed in this review. The findings suggest that future work should consider industrial engineering integrated with OR techniques, with an aim to improving the handling of multiple scopes within one model, while encouraging interaction between the disjoint care levels and with a more direct focus on patient outcomes. Achieving this would continue to bridge the gap between OR, IS and industrial engineering, for clinical pathways to aid decision support.

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An agent-based model for quantitatively analyzing and predicting the complex behavior of emergency departments

Cited by 36 publications

References 38 publications

A systematic literature review of simulation models for non-technical skill training in healthcare logistics

A systematic literature review of simulation models for non-technical skill training in healthcare logistics

Methodological Approaches to Support Process Improvement in Emergency Departments: A Systematic Review

Clinical pathway modelling: a literature review

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