Mortality attributed to complications of surgical operations in the United States: a retrospective cohort study of death certificate data, 1999-2024.

BACKGROUND

Complications of surgical operations remain an important contributor to preventable mortality, despite advances in perioperative care, anesthesia, and surgical safety. However, long-term national mortality trends and demographic disparities associated with surgical complications remain poorly characterized at the population level.

METHODS

We conducted a retrospective analysis of U.S. mortality data from the CDC WONDER Multiple Cause of Death database between 1999 and 2024. Deaths attributed to complications of surgical operations were identified using ICD-10 Y83 codes. Age-adjusted mortality rates (AAMRs) per 100 000 population were calculated using the 2000 U.S. standard population. Temporal trends were evaluated using Joinpoint regression analysis to estimate annual percentage changes (APCs) with 95% confidence intervals (CIs). Mortality patterns were stratified by sex, race/ethnicity, census region, urbanization status, and state.

RESULTS

A total of 470 098 deaths were attributed to complications of surgical operations during the study period. The overall AAMR was 5.3 (95% CI: 5.2-5.4). Mortality declined significantly from 8.1 in 1999 to 3.4 in 2015 (APC: -5.56, P < 0.000001), increased sharply to 7.9 in 2021 (APC: 16.20, P < 0.000001), and subsequently declined to 3.2 in 2024 (APC: -31.85, P < 0.000001). Men demonstrated consistently higher mortality than women (6.7 vs. 4.3 per 100 000). Non-Hispanic Black and American Indian/Alaska Native populations had the highest mortality rates, whereas Asian or Pacific Islander populations had the lowest. Mortality was higher in non-metropolitan areas and in several Southern and Midwestern states.

CONCLUSION

Mortality associated with complications of surgical operations in the United States has demonstrated substantial temporal variation and persistent demographic and geographic disparities between 1999 and 2024. Further studies using patient-level clinical datasets are needed to clarify the underlying contributors to these patterns and identify potential targets for intervention.