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Impact of extreme weather events on healthcare utilization and mortality in the United States

Nature Medicine volume 30, pages 1118–1126 (2024)Cite this article

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Abstract

Climate change is intensifying extreme weather events. Yet a systematic analysis of post-disaster healthcare utilization and outcomes for severe weather and climate disasters, as tracked by the US government, is lacking. Following exposure to 42 US billion-dollar weather disasters (severe storm, flood, flood/severe storm, tropical cyclone and winter storm) between 2011 and 2016, we used a difference-in-differences (DID) approach to quantify changes in the rates of emergency department (ED) visits, nonelective hospitalizations and mortality between fee-for-service Medicare beneficiaries in affected compared to matched control counties in post-disaster weeks 1, 1–2 and 3–6. Overall, disasters were associated with higher rates of ED utilization in affected counties in post-disaster week 1 (DID of 1.22% (95% CI, 0.20% to 2.25%; P < 0.020)) through week 2. Nonelective hospitalizations were unchanged. Mortality was higher in affected counties in week 1 (DID of 1.40% (95% CI, 0.08% to 2.74%; P = 0.037)) and persisted for 6 weeks. Counties with the greatest loss and damage experienced greater increases in ED and mortality rates compared to all affected counties. Thus, billion-dollar weather disasters are associated with excess ED visits and mortality in Medicare beneficiaries. Tracking these outcomes is important for adaptation that protects patients and communities, health system resilience and policy.

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Fig. 1: Map of US counties affected by short-term NOAA NCEI billion-dollar weather disasters included in the analysis (2011–2016).
Fig. 2: Forest plots of ED visit and mortality relative change and DID for affected counties in post-disaster weeks 1–2 and weeks 3–6 in Medicare beneficiaries exposed to a short-term NOAA NCEI billion-dollar weather disaster in the United States.

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Data availability

Healthcare utilization and outcome data for all analyses were based on administrative data for FFS Medicare beneficiaries. These data cannot be shared by the authors due to regulations, but they can be acquired or purchased from Centers for Medicare and Medicaid Services. The NOAA NCEI data on billion-dollar weather and climate disasters are publicly available. SHELDUS cannot be shared by authors due to regulations, but it can be acquired or purchased from Arizona State University.

Code availability

The code is available at GitHub and can be found at https://github.com/Billion-Dollar-Weather-Medicare/ED-Hospitalizations-Mortality/.

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Acknowledgements

We acknowledge support for this research from the Burke Global Health Fellowship at the Harvard Global Health Institute, the Clinician-Teacher Development Award at the Center for Diversity and Inclusion at Massachusetts General Hospital, and the Yerby Fellowship at the Harvard T.H. Chan School of Public Health. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the paper. We also acknowledge the contributions of K. Riley (Weill Cornell Medicine), L. Testa (Harvard Global Health Institute) and K. Phouyaphone (Massachusetts General Hospital) to this paper.

Author information

Authors and Affiliations

  1. Massachusetts General Hospital, Department of Emergency Medicine, Boston, MA, USA

    Renee N. Salas

  2. Harvard Medical School, Boston, MA, USA

    Renee N. Salas & Laura G. Burke

  3. Harvard Global Health Institute, Cambridge, MA, USA

    Renee N. Salas

  4. Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Renee N. Salas, Laura G. Burke, Jessica Phelan & E. John Orav

  5. Beth Israel Deaconess Medical Center, Department of Emergency Medicine, Boston, MA, USA

    Laura G. Burke

  6. Boston University School of Public Health, Center for Climate and Health, Boston, MA, USA

    Gregory A. Wellenius

  7. Brown University School of Public Health, Providence, RI, USA

    Ashish K. Jha

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Contributions

R.N.S., L.G.B., J.P., G.A.W., E.J.O. and A.K.J. designed the study. J.P. and E.J.O. analyzed data. R.N.S., L.G.B., J.P., G.A.W., E.J.O. and A.K.J. interpreted data. R.N.S., L.G.B., J.P., G.A.W., E.J.O. and A.K.J. wrote the paper. All authors reviewed, edited and approved the final paper.

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Correspondence to Renee N. Salas.

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Competing interests

R.N.S. reports no relevant disclosures or grants. L.G.B. reports receiving grant funding from the Association of American Medical Colleges, the National Institutes of Health National Institute on Aging (R56AG075017), and the Agency for Healthcare Research and Quality (R01HS029781), as well as consulting fees from the Emergency Medicine Policy Institute. G.A.W. reports receiving consulting income from the Health Effects Institute and Google. J.P. and E.J.O. report no relevant disclosures or grants. A.K.J. was on leave from Brown University while serving as the White House COVID-19 Response Coordinator. However, this research and work was completed while A.K.J. was employed at the Harvard T.H. Chan School of Public Health and Brown University School of Public Health, and the findings and views in this paper do not reflect the official views or policy of the White House during the tenure of A.K.J. there. A.K.J. otherwise reports no relevant disclosures or grants.

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Nature Medicine thanks Pierre Masselot, Zhenyu Zhang, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Ming Yang, in collaboration with the Nature Medicine team.

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Extended data

Extended Data Fig. 1 Map of NOAA NCEI billion-dollar weather and climate disasters included in the analysis (2011–2016) which includes wildfires and droughts that were considered in our selection of controls.

The color of the county designates the number of long-term drought or wildfires events and the number of short-term events that included flood, flood/severe storm, severe storm, tropical cyclone, and winter storms during the study period of January 1, 2011 – December 31, 2016. U.S., United States; NOAA, National Oceanic and Atmospheric Administration; NCEI, National Centers for Environmental Information.

Extended Data Fig. 2 Forest plot of non-elective hospitalization relative change and difference-in-differences for affected counties in post-disaster Weeks 1-2 and Weeks 3–6 in Medicare beneficiaries exposed to a short-term NOAA NCEI billion-dollar weather disaster in the U.S.

A forest plot of non-elective hospitalization relative change and difference-in-differences with 95% CI in 271,253,459 non-unique U.S. Medicare beneficiaries in 4,884 affected counties and 18,437 control counties for weeks 1-2 and 3–6 for 42 aggregated overall and each NOAA NCEI billion-dollar disaster category (floods, floods/severe storms, severe storms, tropical cyclones, winter storms). CI – 95% confidence interval (mean ± 1.96*SEM); U.S., United States; ED, emergency department; NOAA, National Oceanic and Atmospheric Administration; NCEI, National Centers for Environmental Information.

Extended Data Table 1 Characteristics of U.S. NOAA NCEI long-term billion-dollar weather and climate disasters (wildfire and drought) for affected counties for 2011–2016 that were accounted for in selection of controls
Full size table
Extended Data Table 2 Number of estimated excess ED visits, non-elective hospitalizations, and deaths in Medicare beneficiaries associated with an average-sized U.S. NOAA NCEI billion-dollar weather disaster included in the study between 2011–2016 in post-disaster week 1
Full size table
Extended Data Table 3 Comparison of ED visits, non-elective hospitalizations, and mortality in Medicare beneficiaries in affected versus control counties for post-disaster weeks 1-2 after onset of short-term U.S. NOAA NCEI billion-dollar weather disasters
Full size table
Extended Data Table 4 Comparison of ED visits, non-elective hospitalizations, and mortality in Medicare beneficiaries in affected versus control counties for post-disaster weeks 3–6 after onset of short-term U.S. NOAA NCEI billion-dollar weather disasters
Full size table
Extended Data Table 5 Comparison of ED visits, non-elective hospitalizations, and mortality in Medicare beneficiaries in affected versus control counties for the warning period, or the week before the onset of a short-term U.S. NOAA NCEI billion-dollar weather disasters (days −1 to −7)
Full size table
Extended Data Table 6 Clinical classification software (CCS) categories for ED visits in Medicare beneficiaries during the warning pre-period and warning period for U.S. NOAA NCEI billion-dollar winter storms
Full size table
Extended Data Table 7 Comparison of quartile 4 (most impacted) ED visits, non-elective hospitalizations, and mortality in Medicare beneficiaries in affected versus control counties for the warning period (days −1 to −7) before the onset of a short-term U.S. NOAA NCEI billion-dollar weather disasters
Full size table
Extended Data Table 8 Sensitivity analysis examining post-disaster week 1 ED visits, non-elective hospitalizations, and mortality in Medicare beneficiaries following exposure to a short-term U.S. NOAA NCEI billion-dollar weather disasters when matching based on NOAA climate region
Full size table

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Salas, R.N., Burke, L.G., Phelan, J. et al. Impact of extreme weather events on healthcare utilization and mortality in the United States. Nat Med 30, 1118–1126 (2024). https://doi.org/10.1038/s41591-024-02833-x

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