Minimizing an important part of hospital costs through the optimal allocation of the number of nursing force to different days of the week using linear programming model : Case study in hospital emergency department (A) in Isfahan

Publish Year: 1395
نوع سند: مقاله کنفرانسی
زبان: English
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AMSCONF04_191

تاریخ نمایه سازی: 6 اسفند 1395

Abstract:

Introduction : the hospital as the largest health care center of the society allocates a bulk of the sources and credits assigned to the health sector of the country. Several studies carried out by the researchers indicate that the manpower cost of each hospital constitutes over sixty per cent of its resources. Due to the relevance of the personnel in the quality of services provided to the patients and its costs for hospital, determining the number of optimal needed employees of hospital complex departments is a problem; it has not had a specified standard. Therefore, this research has been carried out for reducing the hospital costs to minimum through the optimization of the nursing force allocation using the Linear programming model in the hospital emergency department. This case study was conducted in 2015.Method : this is a scientific-applied and cross-sectional-descriptive study that has been done in a public health training Centre in 2015; the emergency department was randomly selected as a sample. At the beginning a model was made based on the Linear programming and then the information was collected from the hospital reception during the months of April to September. After calculating the average patients in each day of the week, the optimal number of nurses of different days of the department was determined by the use of Win QSB software.Findings: according to the obtained results, the optimal number of the required nurses by days of week and on the whole is as follows:36=8+4+6+2+7+3+6Conclusion: the Linear programming model can be used as a useful tool for timing and determining the optimal number of employees needed by the various departments of a hospital and reduce costs to minimum.

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Authors

Abbas Sheikh Aboumasoudi

Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran

Ali Sheikh Aboumasoudi

Department of Industrial Engineering, Lenjan Branch, Islamic Azad University, Isfahan, Iran

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