利用非临床数据进行过程模拟,以优化国家卫生部门的临床护理

M. P. W. Sahabandu, R. Hewapathirana, A. Jayatilleke
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引用次数: 0

摘要

导言:斯里兰卡是一个发展中国家,卫生部门的资源有限。在门诊部(OPD)和初级护理单位(PCU)尤其如此。这可以通过识别护理过程中的瓶颈,有效地利用现有资源来克服。过程模拟是一种在世界范围内用于类似目的的流行方法。卫生部门的非临床数据,即等待时间和提供服务的时间,可作为这一方法的变量。该研究的目的是设计一个基于非临床数据的过程模拟,以优化斯里兰卡国有部门卫生机构的紧急护理医疗服务。方法:对斯里兰卡国立医院事故和骨科服务部(AOS)和帕纳杜拉基地医院PCU目前的首次接触医疗系统进行分析,以确定用于时域模拟的资源分配的时间维度。在AOS中使用Arena®软件进行过程仿真和建模。结果:上午OPD - AOS出现堵塞。这种情况主要发生在x光科,因为85%的门诊患者被要求拍x光片。增加医生或药剂师的数量并没有减少等待时间。然而,通过将x光站从一个增加到两个,观察到等待时间减少(从97分钟减少到1分钟)。结论:过程模拟可用于识别临床护理路径中的延迟,从而在医院环境中有效地分配和利用资源。在像斯里兰卡这样财政资源有限的发展中国家,实施这一进程可能是有利的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Process simulation using non-clinical-data to optimize clinical care in the State Health Sector
Introduction: Sri Lanka is a developing country, the resources in health sector is limited. This is particularly true in Outpatient Departments (OPD) and Preliminary Care Units (PCU). This can be overcome by utilizing available resources efficiently by identifying bottle necks in care delivery process. Process simulation is a popular approach used worldwide for similar purposes. Non–clinical–data in health sector i.e. waiting time and service delivery time could be used as variables in this approach. The objective of the study was to design a process simulation based on non-clinical-data for optimization of emergency care medical services in the state sector health institutions in Sri Lanka. Methodology: An analysis of the current first contact care systems in the Accident and Orthopaedic Service (AOS) of the National Hospital of Sri Lanka and PCU at Base Hospital, Panadura was carried out to identify the temporal dimension of resource allocation for time-domain simulation. Process simulation & modelling was done in the AOS by using Arena® software. Results: Congestion was observed in the OPD - AOS in the morning hours. This was mainly at the X-ray department, as 85% of total OPD patients were directed to take X-rays. There was no reduction in waiting time observed by increasing the number of doctors or pharmacists. However, there was a reduction of waiting time (from 97 minutes to 1 minute) observed by increasing X-ray stations from one to two. Conclusions: Process simulation can be used to identify the delays in the clinical care pathway and hence, to allocate & utilize resources effectively & efficiently in hospital settings.   Implementation of this process can be advantageous in developing countries like Sri Lanka, where there are limited financial resources.
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