私营医疗机构人力资源管理分析

Yiannis Kavvadas, Efstathios Kirkos
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引用次数: 0

摘要

希腊私营医疗保健部门主要由中小型实体组成。这些实体,特别是小型实体,完全依靠人力资源。然而,它们似乎没有利用新的技术方法和工具来评估其人力资源。本研究的目的是创建一种方法,以帮助这些实体适当地评估其雇员,并证明通过采用数据挖掘方法可以提高管理人员和负责人的经验知识,以便创建一个成功的评估模型。在本研究中,选择了一个由287名员工组成的医疗保健单位。对12位经理和负责人进行了12次访谈。由八个定性属性组成的图形评定量表Τable被给予受访者。这8个定性属性与18个定量属性相结合,以创建一个新的模型。数据是从人力资源部收集的。为了进行分析,使用了机器学习方法。该模型被证明是有效的,能够为管理层提供有效的信息,供员工评估。数据挖掘方法对人力资源部门和单位行政管理非常有用。上述方法为适当的员工评估提供了低成本和可用的工具。EL分类:J24, M12, M54, C38。关键词:人力资源,管理,医疗单位,数据挖掘
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Human Resources Management Analytics in Private Healthcare Unit
Private Greek healthcare sector consists mainly of medium and small size entities. These entities, especially small ones, rely completely on their Human Resources.  However, it seems that they do not avail themselves of new technological methods and tools for assessing their human resources. The aim of the present study was to create a methodology that will help these entities to evaluate their employees properly and to prove that the empirical knowledge of managers and heads can be enhanced by employing Data Mining methods, in order to create a successful evaluation model. In the present study, a healthcare unit consisted of 287 employees was selected. Twelve interviews were conducted with 12 managers and heads. A Graphic Rating Scale Τable, built by eight qualitative attributes, was given to the interviewees. Those 8 qualitative attributes were combined with 18 quantitative attributes in order for a new model to be created. Data were collected from the Human Resources department. To perform the analysis, Machine Learning methods were used. This model proved to be functional and capable of giving valid information to management for employees’ evaluation. Data Mining methods are quite useful for the HR department and the Administration of the unit. The above methodology provides low-costs and usable tools, for appropriate employees’ evaluation.   EL Classifications: J24, M12, M54, C38. Key words: Human Resources, Management, Healthcare Unit, Data Mining  
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