Abstract / Summary
Background/Objectives: Limited emergency-care resources require priorities based not only on mortality rates or death counts but also on the potential mortality reduction under explicit targets. We applied the age- and sex-standardized domestic short- and mid-term components of a stepwise treatable-death framework across severe emergency conditions in Korea. Methods: This retrospective nationwide study used NEDIS aggregate data from 16 regions during 2018–2022. The 20 conditions with the highest numbers of in-hospital deaths were represented as 17 groups by replacing sepsis (A41), bacterial pneumonia (J15), pneumonia of unspecified organism (J18), and pneumonitis due to solids and liquids (J69) with an extended-sepsis composite. Treatable deaths were the positive difference between observed and target-based expected deaths. National rates in 10-year age-group and sex strata were applied to regional distributions. The short-term target assumed that regions with an age- and sex-standardized mortality ratio (SMR) above 1.0 achieved the national reference level (SMR = 1.0), whereas the mid-term target assumed that all regions achieved the lowest regional SMR for the corresponding condition and year. Five-year cumulative estimates were the primary outcome measure. Results: Across the 17 groups, summed condition-level patient counts totaled 3,384,529 and in-hospital deaths totaled 357,404 (ratio of summed death counts to summed patient counts, 10.56%). Five-year cumulative short-term estimates were highest for extended sepsis (2387), bronchus and lung cancer (1984), and cardiac arrest (1662). Mid-term estimates were highest for cardiac arrest (21,547), extended sepsis (19,340), and severe trauma (7010). Conclusions: After accounting for regional differences in age and sex distributions, extended sepsis remained the condition with the largest short-term and the second-largest mid-term treatable-death burden, supporting its consideration for further policy-priority evaluation. Each treatable-death estimate is an operational policy-scenario estimate rather than an estimate of causally preventable mortality.