The purpose of this research study was to design and pilot a predictive hiring model to improve the hospital's operational vacancy rate and reduce premium pay expenses.
According to Purcell, the average nursing turnover rate is at 18.2%, and the new-graduate nurse turnover rate is higher at 35%. With turnover rates high for nurses, the importance of recruiting, hiring, and training the new nurse needs to be completed as soon as possible. Often, a nurse manager cannot interview and hire into a position until it is vacated. Premium pay including overtime is typically used to cover the time from the position being vacated until the next nurse is trained.
This was a pretest/posttest design with a predictive hiring model intervention. The intervention was a 3-pronged approach that consisted of a strategy for recruiting graduate nurses, hiring to operation vacancy rates, and utilizing a predictive hiring method. Operational vacancy is a calculation to determine if a department has the right amount of hired labor available to work scheduled shifts without having to routinely rely on agency nurses and/or premium pay. These are people ready to work.
The hospital significantly decreased premium pay and eliminated the use of agency nurses by implementing a predictive hiring model tailored to the department's operational vacancy.
A predictive model is a useful vehicle in assisting nurse managers to plan and replace positions more quickly. The model needs continued testing to support application beyond the testing site.