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A data-integrated simulation-based optimization for assigning nurses to patient admissions.
Sundaramoorthi, Duraikannan; Chen, Victoria C P; Rosenberger, Jay M; Kim, Seoung Bum; Buckley-Behan, Deborah F.
Afiliación
  • Sundaramoorthi D; Steven L. Craig School of Business, Missouri Western State University, St. Joseph, MO, USA. dsundaramoorthi@missouriwestern.edu
Health Care Manag Sci ; 13(3): 210-21, 2010 Sep.
Article en En | MEDLINE | ID: mdl-20715305
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.
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Banco de datos: MEDLINE Asunto principal: Admisión del Paciente / Admisión y Programación de Personal / Personal de Enfermería en Hospital Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Health Care Manag Sci Asunto de la revista: SERVICOS DE SAUDE Año: 2010 Tipo del documento: Article País de afiliación: Estados Unidos
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Banco de datos: MEDLINE Asunto principal: Admisión del Paciente / Admisión y Programación de Personal / Personal de Enfermería en Hospital Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Health Care Manag Sci Asunto de la revista: SERVICOS DE SAUDE Año: 2010 Tipo del documento: Article País de afiliación: Estados Unidos