Biomedical Engineering Graduate Program, American University of Sharjah, Sharjah UAE.
Engineering Systems Management, American University of Sharjah, Sharjah UAE.
J Prim Care Community Health. 2024 Jan-Dec;15:21501319241260351. doi: 10.1177/21501319241260351.
Health emergency outbreaks such as the COVID-19 pandemic make it challenging for healthcare systems to ration medical resources and patient care. Such disastrous events have been increasing over the past years and are becoming inevitable, necessitating the need for healthcare to be well-prepared and resilient to unpredictable rises in demand. Quantitative and qualitative based decision support systems increase the effectiveness of planning, alleviating uncertainties associated with the crisis. This study aims to understand how the COVID-19 pandemic has affected the performance of healthcare systems in different areas and to address the associated disruption. A cross-sectional online survey was conducted in the Kingdom of Saudi Arabia and the United Arab Emirates among healthcare workers who worked during the pandemic. The pandemic-related disruption and its psychometric properties were assessed using Structural Equations Modeling (SEM) with 5 latent factors: Staff Mental Health, Communication Level, Planning and Readiness, Healthcare Supply Chain, and Telehealth. Responses from highly qualified participants with many years of experience in hospital settings were collected and analyzed. Results show that the model satisfactorily fits the data with a CLI of 0.91 and TLI of 0.88. The model indicates that enhancing supply chain management, planning, telehealth usage, and communication level across the healthcare system can mitigate the disruption. However, the lack of mental health management for healthcare workers can significantly disrupt the quality of delivered care. Staff mental health and healthcare supply chain, respectively, are the highest contributors to varying degrees of disruption in healthcare delivery. This study provides a direction for more research focusing on determinants of healthcare efficiency. It also provides decision-makers insights into the main factors leading to disruptions in healthcare systems, allowing them to shape their outbreak response and better prepare for future health emergencies.
突发卫生事件，如 COVID-19 大流行，使得医疗系统难以对医疗资源和患者护理进行合理分配。近年来，此类灾难性事件不断增加，且不可避免，这就需要医疗保健做好充分准备，对需求的不可预测增长保持弹性。基于定量和定性的决策支持系统提高了规划的有效性，减轻了与危机相关的不确定性。本研究旨在了解 COVID-19 大流行如何影响不同地区医疗系统的性能，并解决相关的中断问题。在沙特阿拉伯王国和阿拉伯联合酋长国，对在大流行期间工作的医护人员进行了横断面在线调查。使用结构方程建模（SEM）和 5 个潜在因素来评估与大流行相关的中断及其心理测量特性：员工心理健康、沟通水平、计划和准备、医疗保健供应链和远程医疗。收集并分析了来自具有多年医院工作经验的高素质参与者的回复。结果表明，该模型以 CLI 为 0.91 和 TLI 为 0.88 较好地拟合了数据。该模型表明，增强整个医疗系统的供应链管理、规划、远程医疗使用和沟通水平可以减轻中断。然而，缺乏对医护人员心理健康的管理可能会严重扰乱所提供的护理质量。员工心理健康和医疗保健供应链分别是导致医疗服务提供中断的主要因素，其程度不同。本研究为更专注于医疗保健效率决定因素的研究提供了方向。它还为决策者提供了对导致医疗系统中断的主要因素的深入了解，使他们能够塑造他们的疫情应对措施，并为未来的卫生紧急情况做好更好的准备。
