Healthcare system resilience and adaptability to pandemic disruptions in the United States
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866914934170845184 |
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| author | Zhong, Lu Lopez, Dimitri Pei, Sen Gao, Jianxi |
| author_facet | Zhong, Lu Lopez, Dimitri Pei, Sen Gao, Jianxi |
| contents | 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 for each system to adapt to past disruptions. We generalize the quantification framework and find that the US healthcare systems exhibit substantial adaptability but only a moderate level of resilience. 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 is 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_01454 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Healthcare system resilience and adaptability to pandemic disruptions in the United States Zhong, Lu Lopez, Dimitri Pei, Sen Gao, Jianxi Social and Information Networks Physics and Society 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 for each system to adapt to past disruptions. We generalize the quantification framework and find that the US healthcare systems exhibit substantial adaptability but only a moderate level of resilience. 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 is 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. |
| title | Healthcare system resilience and adaptability to pandemic disruptions in the United States |
| topic | Social and Information Networks Physics and Society |
| url | https://arxiv.org/abs/2409.01454 |