A data-integrated simulation-based optimization for assigning nurses to patient admissions

Duraikannan Sundaramoorthi; Victoria C.P. Chen; Jay M. Rosenberger; Seoung Bum Kim; Deborah F. Buckley-Behan

doi:10.1007/s10729-009-9124-9

A data-integrated simulation-based optimization for assigning nurses to patient admissions

Duraikannan Sundaramoorthi, Victoria C.P. Chen, Jay M. Rosenberger, Seoung Bum Kim, Deborah F. Buckley-Behan

School of Industrial Management Engineering

Research output: Contribution to journal › Article › peer-review

24 Citations (Scopus)

Abstract

The health care system in the United States has a shortage of nurses. A careful planning of nurse resources is needed to ease the health care system from the burden of the nurse shortage and standardize nurse workload. An earlier research study developed a data-integrated simulation to evaluate nurse-patient assignments (SIMNA) at the beginning of a shift based on a real data set provided by a northeast Texas hospital. In this research, with the aid of the same SIMNA model, two policies are developed to make nurse-to-patient assignments when new patients are admitted during a shift. A heuristic (HEU) policy assigns a newly-admitted patient to the nurse who has performed the least assigned direct care among all the nurses. A partially-optimized (OPT) policy seeks to minimize the difference in workload among nurses for the entire shift by estimating the assigned direct care from SIMNA. Results comparing HEU and OPT policies are presented.

Original language	English
Pages (from-to)	210-221
Number of pages	12
Journal	Health Care Management Science
Volume	13
Issue number	3
DOIs	https://doi.org/10.1007/s10729-009-9124-9
Publication status	Published - 2010 Sept

Keywords

Nurse assignment
Patient assignment
Simulation-based optimization

ASJC Scopus subject areas

Medicine (miscellaneous)
Health Professions(all)

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10.1007/s10729-009-9124-9

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title = "A data-integrated simulation-based optimization for assigning nurses to patient admissions",

abstract = "The health care system in the United States has a shortage of nurses. A careful planning of nurse resources is needed to ease the health care system from the burden of the nurse shortage and standardize nurse workload. An earlier research study developed a data-integrated simulation to evaluate nurse-patient assignments (SIMNA) at the beginning of a shift based on a real data set provided by a northeast Texas hospital. In this research, with the aid of the same SIMNA model, two policies are developed to make nurse-to-patient assignments when new patients are admitted during a shift. A heuristic (HEU) policy assigns a newly-admitted patient to the nurse who has performed the least assigned direct care among all the nurses. A partially-optimized (OPT) policy seeks to minimize the difference in workload among nurses for the entire shift by estimating the assigned direct care from SIMNA. Results comparing HEU and OPT policies are presented.",

keywords = "Nurse assignment, Patient assignment, Simulation-based optimization",

author = "Duraikannan Sundaramoorthi and Chen, {Victoria C.P.} and Rosenberger, {Jay M.} and Kim, {Seoung Bum} and Buckley-Behan, {Deborah F.}",

note = "Funding Information: Acknowledgements This research was supported by the Robert Wood Johnson Foundation grant number 053963. The first author gratefully acknowledges summer research grant from Steven L. Craig School of Business which enabled the successful completion of this research. The authors thank three anonymous reviewers and the editor-in-chief for a constructive review process and useful comments.",

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N1 - Funding Information: Acknowledgements This research was supported by the Robert Wood Johnson Foundation grant number 053963. The first author gratefully acknowledges summer research grant from Steven L. Craig School of Business which enabled the successful completion of this research. The authors thank three anonymous reviewers and the editor-in-chief for a constructive review process and useful comments.

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A data-integrated simulation-based optimization for assigning nurses to patient admissions

Abstract

Keywords

ASJC Scopus subject areas

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