PURPOSE: This article examines factors that distinguish nursing facilities with very high and very low nursing assistant turnover rates from a middle referent group, exploring the possibility that high and low turnover are discrete phenomena with different antecedents. DESIGN AND METHODS: Data from a stratified sample of facilities in eight states, with directors of nursing as respondents (N = 288), were merged with facility-level indicators from the On-Line Survey Certification of Automated Records and county-level data from the Area Resource File. Multinominal logistic regression was used to identify factors associated with low (less than 6.6% in 6 months) and high (more than 64% in 6 months) turnover rates. RESULTS: With the exception of registered nurse turnover rate, low turnover and high turnover were not associated with the same factors. IMPLICATIONS: Future studies of facility turnover should avoid modeling turnover as a linear function of a single set of predictors in order to provide clearer recommendations for practice.
PURPOSE: This article examines factors that distinguish nursing facilities with very high and very low nursing assistant turnover rates from a middle referent group, exploring the possibility that high and low turnover are discrete phenomena with different antecedents. DESIGN AND METHODS: Data from a stratified sample of facilities in eight states, with directors of nursing as respondents (N = 288), were merged with facility-level indicators from the On-Line Survey Certification of Automated Records and county-level data from the Area Resource File. Multinominal logistic regression was used to identify factors associated with low (less than 6.6% in 6 months) and high (more than 64% in 6 months) turnover rates. RESULTS: With the exception of registered nurse turnover rate, low turnover and high turnover were not associated with the same factors. IMPLICATIONS: Future studies of facility turnover should avoid modeling turnover as a linear function of a single set of predictors in order to provide clearer recommendations for practice.
Authors: Clara Berridge; Julie Lima; Margot Schwartz; Christine Bishop; Susan C Miller Journal: J Am Med Dir Assoc Date: 2020-03-16 Impact factor: 4.669
Authors: Dana B Mukamel; William D Spector; Rhona Limcangco; Ying Wang; Zhanlian Feng; Vincent Mor Journal: Med Care Date: 2009-10 Impact factor: 2.983