Browse > Article
http://dx.doi.org/10.15207/JKCS.2018.9.9.431

Artificial Intelligence to forecast new nurse turnover rates in hospital  

Choi, Ju-Hee (Pusan National University Hospital)
Park, Hye-Kyung (Pusan National University Hospital)
Park, Ji-Eun (Pusan National University Hospital)
Lee, Chang-Min (Convergence Medical Institute of Technology, Pusan National University Hospital)
Choi, Byung-Gwan (College of Medicine, Pusan National University)
Publication Information
Journal of the Korea Convergence Society / v.9, no.9, 2018 , pp. 431-440 More about this Journal
Abstract
In this study, authors predicted probability of resignation of newly employed nurses using TensorFlow, an open source software library for numerical computation and machine learning developed by Google, and suggested strategic human resources management plan. Data of 1,018 nurses who resigned between 2010 and 2017 in single university hospital were collected. After the order of data were randomly shuffled, 80% of total data were used for machine leaning and the remaining data were used for testing purpose. We utilized multiple neural network with one input layer, one output layer and 3 hidden layers. The machine-learning algorithm correctly predicted for 88.7% of resignation of nursing staff with in one year of employment and 79.8% of that within 3 years of employment. Most of resigned nurses were in their late 20s and 30s. Leading causes of resignation were marriage, childbirth, childcare and personal affairs. However, the most common cause of resignation of nursing staff with in one year of employment were maladaptation to the work and problems in interpersonal relationship.
Keywords
Artificial intelligence; Tensorflow; New nurses; Strategic human resources management; Turnover rates;
Citations & Related Records
Times Cited By KSCI : 8  (Citation Analysis)
연도 인용수 순위
1 E. J. Yeun, Y. M. Kwon, M. S. Jeon & J. H. An. (2016). Factors Influencing Hospital Nurses' Turnover Intention: A Cross-sectional Survey. Journal of Korea Contents Society, 16(1), 94-106.
2 J. H. Park & M. H. Lee. (2017). Effect of a practical work-oriented education program on the ability of newly recruited nurses in execution of clinical competency, critical thinking and turnover rate. Journal of Digital Convergence, 15(7), 191-199.   DOI
3 S. S. Han, I. S. Sohn & N. E. Kim. (2009). New nurse turnover intention and influencing factors. Journal of Korean Academy Nursing, 39(6), 78-87.
4 M. L. Park & M. J. Lee. (2018). Effect of mentoring program's development about new nurses. Journal of Convergence for Information Technology, 8(1), 43-51.   DOI
5 K. J. Oh & E. Y. Kim. (2018). The influence of emotional labor of general hospital nurses on tunover intention: mediationg effect of nursing organizational culture. Journal of Digital Convergence, 16(5), 317-327.   DOI
6 S. O. Choi. (2005). The Development of an Organizational Socialization Process Model for New Nurses using a System Dynamics Approach. Journal of Korean Academy of Nursing, 35(2), 323-335.   DOI
7 E. A. Jo & J. Y. Kang. (2015). Influence of Workplace Bullying and Resilience on Organizational Socialization in New Gradute Nurses. The Journal of Muscle and Joint Health, 22(2), 78-86.   DOI
8 K. J. Kim. (2012). Human Resource Management System for Nurses: Challenges and Research Directions. The Korean Journal of Health Service Management, 6(1), 247-258. ISSN: 2093-5966.   DOI
9 Hospital Nurses Association. (2012). Survey on the Status of Hospital Nursing Staff Placement. Seoul: Hospital Nurses Association.
10 J. P. Hong, E. J. Kim & H. Y. Park. (2017). An Analysis of Determinants for Artificial Intelligence Industry Competitiveness. Journal of the Korea Institute of Information and Communication Engineering, 21(4), 663-671.   DOI
11 S. W. Son. (2017). Copyright Protection on Artificial Intelligence(AI) generated Works. Journal of Korea Information law, 20(3), 83-110.
12 G. H. Kim, J. Y. Lee & A. S. O. (2013). The Convergence of Medical IT and Big Data. Journal of The Korea Society of Computer & Information, 21(2), 17-25.   DOI
13 J. M. Yang. (2016). A Study on Predictive Crime Analytics based on Artificial intelligence and Police Stop. New Trend of Criminal Law, Vol. 51, 210-242.
14 S. H. Lee. (2016). Artificial Intelligence Platform Competition is beginning. LG Business Insight, 2-16.
15 K. S. Park & S. H. Hwang. (2005). A Study on the Strategic Human Capital for competitive Advantage. Journal of Industrial Economics and Business, 18(5), 1957-1979.
16 J. H. Joo. (2016). How does Artificial Intelligence Change the traffic Environment. Journal of Monthly Transportation, 224, 80-87.
17 K. Y. Lee & J. H. Kim. (2016). Artificial Intelligence Technology Trends and IBM Watson References in the Medical Field. Korean Medical Education Review, 18(2), 51-57.   DOI
18 S. Y. Jin. (2016). The Autonomy of Artificial Intelligence, the Subject of Science Fiction, is coming to the Question of Reality. Journal of LG Business Insight, 2-21.
19 Wright, P. M., & McMahan, G. C. (1992). Theoretical perspectives for strategic human resource management. Journal of Management, 18(2), 295-320.   DOI
20 J. S. Her & Y. S. Yoon. (2009). A Study on the Directionality of Korean-style Strategic Human Resource Management. Korean Business review, 2(1), 223-248.
21 E. R. Song, K. H. Park & J. S. Moon. (2016). The Moderating Effect of Job Embeddedness in the Relationship Between strategic Human Resource Management and Job Competence, Turnover Intention. The Korean Journal of Human Resource Development, 19(1), 73-107.
22 S. Y. Park, Y. H. Kwon & Y. S. Park. (2015). Resilience and Organizational Socialization in New Nurses. Journal of The Korea Contents Society, 15(2), 324-332.
23 W. Lee. (2006). Improvement of Hospital Human Resource Management for Achieving Organizational Goals. The Journal of Korean Hospital Association, 300, 73-83.
24 K. S. Song. (2011). Introduction to Korean Medical Service Industry and Success Factors-Focusing on CEO Leadership and SHRD in Asan Medical center. The Review of Business History, 29(2), 73-120.
25 I. S. Son, H. S. Kim, J. S. Kwon, D. I. Park, Y. H. Han & S. S. Han. (2008). Development of an Instrument to Measure Organizational Socialization of New Clinical Nurses. Journal of Korea Clinical Nursing Research, 14(1), 82-97.
26 D. E. Lee. (2017). Innovation in Artificial Intelligence?: Focused on the Introduction of Watson by Gill. Journal of Science and Technology Policy, 227, 54-61.
27 Guest, D.E. (1989). Personnel anf HRM: can you tell the difference?. Personnel Management, 21, 48-51.
28 Beaumont, P.B. (1993). Human Resource Management: key concepts and skills. Sage Publications Thousand Oaks, Calif.
29 Wright, Smart, & McMahan. (1995). Matches Between Human Resources and Strategy among NCAA Basketball Teams. Academy of Management Journal, 38(4), 1052-1074.   DOI
30 Drucker, P. F. (1990). Management the non-profit organization practices and principles. Harper Colins publishers. Inc, New York, USA.
31 Jeffery Pfeffer. (1998). The Human Equation:Building Profits by Putting People First. Harvard Business School Press. (Translator: S. J. Yoon & S. E. Park, 1998, Human Equation, Seoul: Gypsum).
32 H. K. Jo, T. Y. Lee & C. W. Kim. (2015). Hospital Nurse Turnover Rate and Structural Characteristics of Hospital. Journal of the Korea Academia-Industrial Cooperation Society, 16(1), 453-461.   DOI
33 B. K. Choi, B. S. Gam, K. Y. Hwang, S. H. Seo, J. S. Park, Y. M. Kim, I. S. Park, Y. H. Choi, S. G. Song & S. H. Kang. (2017). Tensorflow Programming Basics. Seoul: Cheong-Gu cultual conpany.
34 H. S. Park & J. H. Ha. (2016). Adaptation Experience of Sleep in New Nurses. The Korean Journal of Fundamentals of Nursing, 23(1), 21-31.   DOI
35 S. A. Kim & H. W. Jeon. (2014). Experience of Turnover in New Nurses. Journal of Korean Society of public Health Nursing, 28(3). 644-657. DOI: 10.5932/JKPHN.2014.28.3.644.   DOI