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.