PDF(Pubmed)
Abstract：
UNASSIGNED: Considering the increasing use of information technology (IT) and the need of the implementation of related projects, the lack of IT specialists in the health system is one of the major challenges that require planning and foreseeing. This study was conducted with the aim of predicting the number of required IT personnel in hospitals of Isfahan University of Medical Sciences based on the modeling of identified and weighed influential factors in 2023.
UNASSIGNED: First, Delphi method and multi-criteria decision-making (MCDM) using the Expository Posthaste Effective Resemblant Tool (ExPERT) were conducted to identify and weigh the components that affect IT staff\'s workload in hospitals. Then, the model for predicting the required number of IT personnel for the involved hospitals was developed. In all stages, the obtained information and results were checked and confirmed using experts\' opinions in Focus Group Discussions.
UNASSIGNED: Twenty-one hospitals (57%) out of 37 hospitals are facing a shortage of IT personnel. This varies from 0.5 to 1.6 personnel in different hospitals. Thirteen hospitals (35%) were reported to have adequate IT staffing and three hospitals (8%) had excess IT staffing.
UNASSIGNED: This study provided a predictive model for required IT staff in hospitals using MCDM through ExPERT which can be used in cases where the use of workload-based methods such as Workload Indicators of Staffing Need is complex or time-consuming.
UNASSIGNED: First, Delphi method and multi-criteria decision-making (MCDM) using the Expository Posthaste Effective Resemblant Tool (ExPERT) were conducted to identify and weigh the components that affect IT staff\'s workload in hospitals. Then, the model for predicting the required number of IT personnel for the involved hospitals was developed. In all stages, the obtained information and results were checked and confirmed using experts\' opinions in Focus Group Discussions.
UNASSIGNED: Twenty-one hospitals (57%) out of 37 hospitals are facing a shortage of IT personnel. This varies from 0.5 to 1.6 personnel in different hospitals. Thirteen hospitals (35%) were reported to have adequate IT staffing and three hospitals (8%) had excess IT staffing.
UNASSIGNED: This study provided a predictive model for required IT staff in hospitals using MCDM through ExPERT which can be used in cases where the use of workload-based methods such as Workload Indicators of Staffing Need is complex or time-consuming.
摘要：
■考虑到信息技术（IT）的使用日益增加以及相关项目实施的需要，卫生系统缺乏IT专家是需要规划和预见的主要挑战之一。这项研究的目的是根据2023年识别和加权影响因素的建模，预测伊斯法罕医科大学医院所需的IT人员数量。
■首先，使用ExpositoryPosthaste有效相似工具（ExPERT）进行德尔菲法和多准则决策（MCDM），以识别和衡量影响医院IT人员工作量的组成部分。然后，建立了预测所涉及医院所需IT人员数量的模型。在所有阶段,所获得的信息和结果在焦点小组讨论中使用专家意见进行检查和确认。
■37家医院中有21家（57%）面临IT人员短缺的问题。不同医院的人员从0.5到1.6不等。据报道，有13家医院（35％）拥有足够的IT人员，有3家医院（8％）拥有过多的IT人员。
本研究通过ExPERT为使用MCDM的医院所需IT人员提供了一个预测模型，该模型可用于使用基于工作负载的方法（例如人员配备需求的工作负载指标）复杂或耗时的情况。
■首先，使用ExpositoryPosthaste有效相似工具（ExPERT）进行德尔菲法和多准则决策（MCDM），以识别和衡量影响医院IT人员工作量的组成部分。然后，建立了预测所涉及医院所需IT人员数量的模型。在所有阶段,所获得的信息和结果在焦点小组讨论中使用专家意见进行检查和确认。
■37家医院中有21家（57%）面临IT人员短缺的问题。不同医院的人员从0.5到1.6不等。据报道，有13家医院（35％）拥有足够的IT人员，有3家医院（8％）拥有过多的IT人员。
本研究通过ExPERT为使用MCDM的医院所需IT人员提供了一个预测模型，该模型可用于使用基于工作负载的方法（例如人员配备需求的工作负载指标）复杂或耗时的情况。
