Date of Award

January 2018

Document Type

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Background: Many hospitals use outdated non-data driven methods for nurse scheduling.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.

Comments

This thesis is restricted to Yale network users only. It will be made publicly available on 09/03/2019

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