Yu Gil Song; Eun Kyoung Yun

doi:10.4040/jkan.2015.45.2.280

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Original Article
Model for Unplanned Self Extubation of ICU Patients Using System Dynamics Approach: Yu Gil Song, Eun Kyoung Yun; Journal of Korean Academy of Nursing 2015;45(2):280-292.
DOI: https://doi.org/10.4040/jkan.2015.45.2.280
Published online: April 30, 2015

¹College of Nursing Science, Kyung Hee University, Seoul, Korea.

²College of Nursing Science·East-West Nursing Research Institute, Kyung Hee University, Seoul, Korea.

Address reprint requests to: Yun, Eun Kyoung. College of Nursing Science, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 130-701, Korea. Tel: +82-2-961-0917, Fax: +82-2-961-9398, ekyun@khu.ac.kr

• Received: October 2, 2014 • Revised: October 19, 2014 • Accepted: February 2, 2015

This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License. (http://creativecommons.org/licenses/by-nd/4.0/) If the original work is properly cited and retained without any modification or reproduction, it can be used and re-distributed in any format and medium.

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Abstract
NOTES
REFERENCES

Abstract

Purpose
In this study a system dynamics methodology was used to identify correlation and nonlinear feedback structure among factors affecting unplanned extubation (UE) of ICU patients and to construct and verify a simulation model.
Methods
Factors affecting UE were identified through a theoretical background established by reviewing literature and preceding studies and referencing various statistical data. Related variables were decided through verification of content validity by an expert group. A causal loop diagram (CLD) was made based on the variables. Stock & Flow modeling using Vensim PLE Plus Version 6.0b was performed to establish a model for UE.
Results
Based on the literature review and expert verification, 18 variables associated with UE were identified and CLD was prepared. From the prepared CLD, a model was developed by converting to the Stock & Flow Diagram. Results of the simulation showed that patient stress, patient in an agitated state, restraint application, patient movability, and individual intensive nursing were variables giving the greatest effect to UE probability. To verify agreement of the UE model with real situations, simulation with 5 cases was performed. Equation check and sensitivity analysis on TIME STEP were executed to validate model integrity.
Conclusion
Results show that identification of a proper model enables prediction of UE probability. This prediction allows for adjustment of related factors, and provides basic data do develop nursing interventions to decrease UE.
Keywords: Airway extubation; Intensive care units; Nonlinear dynamics

This manuscript is a condensed form of the first author's master's thesis from Kyung Hee University.

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Figure 1

Causal loop diagram of unplanned extubation.

Figure 2

Stock & flow diagram of unplanned extubation.

Figure 3

Results of the simulation.

Figure 4

Sensitivity analysis on TIME STEP.

Table 1

Characteristics of Case Patients

Figure & Data

REFERENCES

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