Natural disasters in the United States: Hurricane risk, hospital closures, and healthcare finance

Abstract

Background: Global climate change has increased the likelihood of natural disasters, including hurricanes, floods, wildfires, tornadoes, and earthquakes; this increased risk presents acute socioecological disturbances that generate cascading impacts across healthcare systems, social structures, and economic frameworks. Forty-three percent of Atlantic hurricanes that make U.S. landfall hit the southeastern United States, and their increasing intensity threatens the healthcare infrastructure. Hospital cost-to-charge ratios (CCRs) vary between rural and urban facilities, but hurricane risk impacts on hospital financial performance remain poorly understood.
Objective: To examine relationships among hurricane risk, geographic location, and hospital CCRs among southeastern hospitals.
Methods: A cross-sectional analysis was used to merge 2021 CMS Cost Report data with 2023 FEMA National Risk Index data for 1,030 hospitals across eight southeastern states. All hospitals within this region were included except for federally funded hospitals due to their unique funding model. Each hospital self-reports its categorization of urban or rural on the CMS Cost Report. Multivariate regression was used to examine associations among log-transformed CCR and hurricane risk percentile, rural/urban location, and hospital quick ratio.
Results: Among 1,030 hospitals analyzed, 52% were rural and 48% urban. The regression model explained 24.7% of CCR variation (adjusted R² = 0.2465, F = 85.18, p <.0001). All predictors were statistically significant (p <.0001). Counter to expectations, each 1-point increase in hurricane risk percentile was associated with a 0.1% decrease in CCR, indicating improved cost efficiency in higher-risk areas. LOGCCR = -.75714 -.00840 (NAPCT) -.26551 (RURAL) +.01491 (QUICK) -.00011 (QUICK2). Rural hospitals as indicated by the CMS Cost Report demonstrated 26.5% lower CCR compared to urban hospitals. Hospital quick ratio showed a curvilinear relationship with CCR; at the mean quick ratio (3.819), each 1-unit increase was associated with a 1.4% increase in CCR. No significant multicollinearity was detected among predictor variables.
Conclusions: Hurricane risk is paradoxically associated with lower hospital CCR, suggesting complex financial adaptations in high-risk areas. Rural hospitals maintain more favorable cost structures than urban facilities, and policymakers should consider these geographic variations in disaster preparedness strategies.

Keywords

Cost-to-charge ratio / Disaster preparedness / Hospital finance / Hurricane risk / Rural hospitals

AUTHORS CONTRIBUTIONS

George Audi and Hanadi Hamadi designed the study and wrote the first draft of the manuscript with Margaret Capen and Rima Tawk. George Audi and Hanadi Hamadi developed the statistical analysis plan and George Audi and Margaret Capen performed the statistical analyses. Willie Williams completed the manuscript preparation and editing. Each co-author contributed to either the delivery of the study or helped to devise the protocol. All authors have given final approval for the current version to be published.

FUNDING

This research received no financial support from any organization.

CONFLICTS OF INTEREST DISCLOSURE

The authors declare they have no conflicts of interest.

INFORMED CONSENT

The requirement for written informed consent was waived because of the study’s retrospective design.

ETHICAL STATEMENT

This study was approved by the Institutional Review Board of Florida A&M University (No. 2228446-1) on 06/05/2025 and was conducted per the ethical principles of the Declaration of Helsinki.

ETHICS APPROVAL

The Publication Ethics Committee of the Association for Health Sciences and Education. The journal’s policies adhere to the Core Practices established by the Committee on Publication Ethics (COPE).

PROVENANCE AND PEER REVIEW

Not commissioned; externally double-blind peer reviewed.

DATA AVAILABILITY STATEMENT

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

DATA SHARING STATEMENT

No additional data are available.

OPEN ACCESS

This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).

COPYRIGHTS

Copyright for this article is retained by the author(s), with first publication rights granted to the journal.

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