NURSE STAFFING UNDER DEMAND UNCERTAINTY TO REDUCE COSTS AND ENHANCE PATIENT SAFETY

Author:

DAVIS ASHLEY1,MEHROTRA SANJAY1,HOLL JANE2,DASKIN MARK S.3

Affiliation:

1. Department of Industrial Engineering and Management Sciences, Northwestern University, 2145 Sheridan Road Room C210, Evanston, IL 60208, USA

2. Institute for Healthcare Studies, Feinberg School of Medicine, Northwestern University, 750 N Lake Shore Drive, Rubloff Building, 10th Floor, Chicago, IL 60611, USA

3. Department of Industrial and Operations Engineering, University of Michigan, 1205 Beal Avenue, Ann Arbor, MI 48109, USA

Abstract

Hospitals must maintain safe nurse-to-patient ratios in patient care units to offer adequate and safe patient care. Since the patient demand is highly variable, during high patient demand periods temporary or overtime nurses are hired to ensure safe nurse-to-patient ratios. These overtime nurses incur higher expense, and are often less effective. We study the problem of permanent nurse staffing level estimation under demand uncertainty as a newsvendor model. Our models are based on limited moment information of the demand distribution. Additionally, we introduce the use of asymmetric cost functions representing overstaffing and understaffing nursing costs. Findings using data from the general surgery and intensive care units at hospitals in Chicago, IL and Augusta, GA are presented. Computational results based on publically available cost data show that 3.1% and 7.3% annual cost savings result by introducing salvage value and newsvendor optimization in intensive care and general care units respectively. This new staffing scheme also improves patient safety as shifts are staffed with more permanent nurses.

Publisher

World Scientific Pub Co Pte Lt

Subject

Management Science and Operations Research,Management Science and Operations Research

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