Transformation of potential medical demand in China: A system dynamics simulation model

Yu, Wenya; Li, Meina; Ge, Yang; Li, Ling; Zhang, Yi; Liu, Yuan; Zhang, Lulu

doi:10.1016/j.jbi.2015.08.015

Cited by 31 publications

(39 citation statements)

References 77 publications

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“…Sensitivity analysis was utilized to compare whether the model would fluctuate dramatically after changing some parameters and structures, which can be employed to evaluate the reliability and rationality of a model. 35 The sensitivity of parameters was calculated by DY(t)/Y(t) and DX(t)/X(t), which represented the change of the output variable and the sensitive variables, respectively. Therefore, the formulation of sensitivity analysis was

.…”

Section: Methodsmentioning

confidence: 99%

Research of an emergency medical system for mass casualty incidents in Shanghai, China: a system dynamics model

Yu¹,

Lv²,

Hu³

et al. 2018

PPA

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Objectives Emergency medical system for mass casualty incidents (EMS-MCIs) is a global issue. However, China lacks such studies extremely, which cannot meet the requirement of rapid decision-support system. This study aims to realize modeling EMS-MCIs in Shanghai, to improve mass casualty incident (MCI) rescue efficiency in China, and to provide a possible method of making rapid rescue decisions during MCIs. Methods This study established a system dynamics (SD) model of EMS-MCIs using the Vensim DSS program. Intervention scenarios were designed as adjusting scales of MCIs, allocation of ambulances, allocation of emergency medical staff, and efficiency of organization and command. Results Mortality increased with the increasing scale of MCIs, medical rescue capability of hospitals was relatively good, but the efficiency of organization and command was poor, and the prehospital time was too long. Mortality declined significantly when increasing ambulances and improving the efficiency of organization and command; triage and on-site first-aid time were shortened if increasing the availability of emergency medical staff. The effect was the most evident when 2,000 people were involved in MCIs; however, the influence was very small under the scale of 5,000 people. Conclusion The keys to decrease the mortality of MCIs were shortening the prehospital time and improving the efficiency of organization and command. For small-scale MCIs, improving the utilization rate of health resources was important in decreasing the mortality. For large-scale MCIs, increasing the number of ambulances and emergency medical professionals was the core to decrease prehospital time and mortality. For super-large-scale MCIs, increasing health resources was the premise.

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.…”

Section: Methodsmentioning

confidence: 99%

Research of an emergency medical system for mass casualty incidents in Shanghai, China: a system dynamics model

Yu¹,

Lv²,

Hu³

et al. 2018

PPA

Self Cite

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“…It may provide us with optimized interventions to promote CHSs primary diagnosis, since it can set various levels of patient's visiting behaviour-influencing factors. It may improve the reliability of the model, by setting constraints according to the real world, for instance, increased population generating new demands and the available resource restricting medical service supplying [5][6][7][8][9]. The SD model is built with software Vensim 5.6a (USA, Ventana Systems, Inc.).…”

Section: Methodsmentioning

confidence: 99%

A System Dynamics Simulation Model of Hierarchical Medical Care System Reform in China

Zhang¹,

Liu²,

Yang³

et al. 2017

J Health Med Inform

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The hierarchical medical care system reform in China may lead to drastic changes of medical care utilizations distribution in different medical care subsystems. A medical care system dynamics model was constructed to simulate the intervention scenarios according to the reform measures, and to estimate changes of demands, utilizations distribution and reasonable resources allocation, in order to provide optimized intervention for decision-makers.

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“…A small or partly blockage demonstrates a non-ST elevation myocardial infarction (NSTEMI). Another cause may be spasm of coronary arteries that abandon the blood flow to a part of heart muscle [11]. However, no simulation modeling available until for the Heart patient.…”

Section: Introductionmentioning

confidence: 99%

Simulation modeling for heart attack patient by mapping cholesterol level

George

Gaikwad

2020

IJEECS

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<p>Cholesterol is a complex structural material made up of four-fused hydrocarbon rings. There is a hydrocarbon tail linked at one end of the structure, while the hydroxyl group linked to each other on the other end. To one end of the structure, a hydrocarbon tail linked and to the other end, a hydroxyl group linked to each other. High cholesterol level is one among the major risk factors of a heart attack. It is feasible to compute and control the cholesterol level of a cardiovascular patient by making use of intended Mathematical modeling in System Dynamics (S.D.). Moreover, by simulating proposed set of equations for a heart attack patient, recovery accomplished at a faster pace. Because of S.D., a substantial amount of reduction in the patient's Cardiovascular Disease achieved by control over the sterol level of the heart patient. This simulation modeling is an attempt made in translational research domain and is useful in the healthcare industry health care industry. It will minimize the risk of heart stroke and maintain a healthy life.</p>

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Transformation of potential medical demand in China: A system dynamics simulation model

Cited by 31 publications

References 77 publications

Research of an emergency medical system for mass casualty incidents in Shanghai, China: a system dynamics model

Research of an emergency medical system for mass casualty incidents in Shanghai, China: a system dynamics model

A System Dynamics Simulation Model of Hierarchical Medical Care System Reform in China

Simulation modeling for heart attack patient by mapping cholesterol level

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