Date of Award
1-1-2018
Document Type
Open Access Thesis
Degree Name
Doctor of Nursing Practice (DNP)
Department
Yale University School of Nursing
First Advisor
Margaret L. Holland
Abstract
Objective: This study was designed to develop a model for predicting nurse scheduling needs in a hospital unit based on historical patient census and nurse staffing requirements.
Background: Many hospitals use outdated non-data driven methods for nurse scheduling.
Methods: Historical nurse scheduling and staffing datasets for 2015, 2016, and 2017 from a 33-bed surgical unit in an inner-city urban hospital in Portland, Oregon, were used to build a predictive model for nurse scheduling needs.
Results: The patient census for 2017 was three patients higher than the two previous years and showed a variation in the day of the week, with a consistent weekly trend of more nurses needed at the beginning of the week and fewer needed during the weekend.
Conclusion: Based on model predictions, nurse scheduling in this unit should vary by day of the week, which has not historically been done.
Recommended Citation
Bowie, Danielle, "The Development And Implementation Of A Forecasting Model For Inpatient Nurse Scheduling" (2018). Yale School of Nursing Digital Theses. 1052.
https://elischolar.library.yale.edu/ysndt/1052
This Article is Open Access