A Study on Predicting the Turnover of Nursing Staff of Different Education Backgrounds: Using the Absorbing Markov Chain Method

This study employed the Markov chain to establish a model to predict the turnover of nursing staff of different education backgrounds in Taiwan, which could simulate the number, probability and retention time of nursing staff of various professional levels. The simulation data of this study came from the nursing staff of a large hospital in Taiwan. According to the simulation results, the accuracy of the nursing staff turnover prediction model was up to 94.35~99.93%. The results suggested that, before being promoted to the N3 level, the average retention time of nursing staff was too long and the number of promotions was too small, resulting in an excessively high turnover rate of nursing staff below the N2 level. In addition the turnover rate of nursing staff with a university education background was higher than that of nursing staff with a junior college education. The research findings could provide medical institutions in Taiwan with a reference for the planning of retention and promotion counseling for nursing staff of various professional levels.