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

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)


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 languageEnglish
Pages (from-to)210-221
Number of pages12
JournalHealth Care Management Science
Issue number3
Publication statusPublished - 2010 Sept


  • Nurse assignment
  • Patient assignment
  • Simulation-based optimization

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Health Professions(all)


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