Understanding healthcare system resilience has become paramount, particularly in the wake of the COVID-19 pandemic, which imposed unprecedented burdens on healthcare services and severely impacted public health. Resilience is defined as the system’s ability to absorb, recover from and adapt to disruptions; however, despite extensive studies on this subject, we still lack empirical evidence and mathematical tools to quantify its adaptability (the ability of the system to adjust to and learn from disruptions). By analyzing millions of patients’ electronic medical records across US states, we find that the COVID-19 pandemic caused two successive waves of disruptions within the healthcare systems, enabling natural experiment analysis of the adaptive capacity of each system to adapt to past disruptions. We generalized the quantification framework and found that the US healthcare systems exhibit substantial adaptability (ρ = 0.58) but only a moderate level of resilience (r = 0.70). When considering system responses across racial groups, Black and Hispanic groups were more severely impacted by pandemic disruptions than white and Asian groups. Physician abundance was the key characteristic for determining healthcare system resilience. Our results offer vital guidance in designing resilient and sustainable healthcare systems to prepare for future waves of disruptions akin to COVID-19 pandemics.

了解医疗保健系统的弹性已变得至关重要，特别是在 COVID-19 大流行之后，它给医疗保健服务带来了前所未有的负担，并严重影响了公共卫生。弹性被定义为系统吸收、恢复和适应中断的能力；然而，尽管对这个主题进行了广泛的研究，我们仍然缺乏经验证据和数学工具来量化其适应性（系统适应干扰并从中学习的能力）。通过分析美国各州数百万患者的电子病历，我们发现 COVID-19 大流行在医疗保健系统内造成了两波连续的中断，从而可以对每个系统适应过去中断的适应能力进行自然实验分析。我们概括了量化框架，发现美国医疗保健系统表现出很大的适应性（ρ = 0.58），但只有中等水平的弹性（r = 0.70）。在考虑跨种族群体的系统反应时，黑人和西班牙裔群体比白人和亚裔群体受到大流行破坏的影响更严重。医生的丰富程度是决定医疗保健系统弹性的关键特征。我们的研究结果为设计具有弹性和可持续的医疗保健系统提供了重要指导，以应对未来类似于 COVID-19 大流行的破坏浪潮。