The Development And Implementation Of A Forecasting Model For Inpatient Nurse Scheduling

<p>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.</p> <p>Background: Many hospitals use outdated non-data driven methods for nurse scheduling.</p> <p>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.</p> <p>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.</p> <p>Conclusion: Based on model predictions, nurse scheduling in this unit should vary by day of the week, which has not historically been done.</p>

Name thesis:degree_name

Doctor of Nursing Practice (DNP)

Level thesis:degree_level

Open Access Thesis

Discipline thesis:degree_discipline

Yale University School of Nursing

Year

2018

Author dc:creator

• Bowie, Danielle

Contributors dc:contributor

• Margaret L. Holland

Repository record dc:identifier

https://elischolar.library.yale.edu/ysndt/1052

OAI identifier oai:identifier

oai:elischolar.library.yale.edu:ysndt-1051