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KMID : 0869520230290010068
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Journal of East-West Nirsing Research
2023 Volume.29 No. 1 p.68 ~ p.77
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A Predictive Model of Turnover among Nurses in a Tertiary Hospital: Decision Tree Analysis
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Kang Kyung-Ok
Han Na-Ra
Jeong Jeong-A
Choi Young-Eun
Park Jin-Kyung
Jeong Seok-Hee
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Abstract
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Purpose: The purposes of this study were to develop a predictive model and evaluate this model of turnover in hospital nurses.
Methods: Participants were 1,565 nurses from a tertiary hospital in South Korea. Descriptive statistics and a decision-tree analysis were performed using the SPSS WIN 23.0 program.
Results: The turnover groups were presented in eleven different pathways by decision tree analysis. There were three high-risk groups with a higher turnover rate than the average, and eight low-risk groups with a lower turnover rate. Among them, two low-risk groups had a 0% turnover rate. The groups were classified according to general characteristics such as position, period of temporary position, clinical career at last working unit, total clinical career, and period of leave of absence. The accuracy of the model was 83.2%, sensitivity 63.7%, and specificity 98.1%.
Conclusion: This predictive model of turnover may be used to screen the turnover risk groups and contribute for decreasing the turnover of hospital nurses in South Korea.
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KEYWORD
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Personnel turnover, Nurses, Decision trees
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