首页> 外文会议>Data Mining and Optimization, 2009. DMO '09 >An exploration study of nurse rostering practice at Hospital Universiti Kebangsaan Malaysia
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An exploration study of nurse rostering practice at Hospital Universiti Kebangsaan Malaysia

机译:马来西亚Kebangsaan大学医院的护士名册实践探索研究

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The Nurse Rostering Problem (NRP) is a task of assigning duties fairly among available nurses at healthcare organizations for specific periods of time defined as shifts. NRP belongs to NP-hard problems for which an optimal solution is difficult to be obtained. This paper reports on the practical nurse rostering problem and issues at Hospital Universiti Kebangsaan Malaysia (HUKM). A survey (questionnaire and interviews) was conducted and used as the main tool for gathering primary data concerning the nurses' preferences and other constraints. Furthermore, policy maker views were collected and analyzed. The results identified the majority of rostering problems that the nurses are currently facing at HUKM. The results further revealed that the underlying need for developing an automated fair nurse roster is increasingly becoming critical. Based upon the results, a mathematical model for HUKM nurse rostering problem was formulated. A new objective function was also presented to cope with such a real world problem. Additionally, a new dataset for HUKM was gathered which is readily available for future researches and studies.
机译:护士名册问题(NRP)是一项任务,任务是在定义为轮班的特定时间段内,在医疗机构的可用护士中公平分配职责。 NRP属于NP难题,因此难以获得最佳解决方案。本文报道了马来西亚Kebangsaan大学医院(HUKM)的实际护士名册问题。进行了一项调查(问卷调查和访谈),并用作收集有关护士偏好和其他限制因素的主要数据的主要工具。此外,收集并分析了决策者的观点。结果确定了HUKM护士目前面临的大多数排班问题。结果进一步表明,开发自动化的公平护士名册的基本需求变得越来越重要。根据结果​​,建立了HUKM护士排班问题的数学模型。还提出了一个新的目标函数来应对这种现实问题。此外,还收集了HUKM的新数据集,可随时用于将来的研究和研究。

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