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Development and validation of the excess mortality ratio-based Emergency Severity Index

  • Ki Jeong Hong
  • , Sang Do Shin
  • , Young Sun Ro
  • , Kyoung Jun Song
  • , Adam J. Singer
  • Seoul National University

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Purpose: The purpose of this study is to develop and validate the excess mortality ratio-based Emergency Severity Index (EMR-ESI) that feasibly and objectively assesses the severity of emergency department (ED) patients based on their chief complaints. Methods: We used data from the National Emergency Department Information System of Korea from January 2006 to December 2009. We obtained information on mortality and the corresponding chief complaints exhibited by patients presenting to all EDs. The EMR-ESI was computed from the ratio of sex-age standardized hospital mortality for each chief complaint and the sex-age standardized mortality of the entire population of Korea. We tested the discriminatory power of the EMR-ESI on the prediction of hospital outcomes using the area under the receiver operating characteristic curve (AUC) from a multivariate logistic regression model. This model was adjusted for clinical parameters, and the goodness of fit was estimated using the Hosmer-Lemeshow logistic model. Results: Included in the study were 4 713 462 patients who presented 7557 chief complaint codes from 2006 to 2008. The EMR-ESI had a range of 0 to 6389.45 (mean ± SD, 1.11 ± 4.67; median, 0.70). The adjusted odds ratio of the EMR-ESI (unit, 1.0) for hospital mortality was 1.11 (95% confidence interval, 1.11-1.12). The AUCs for predicting hospital mortality, ED mortality, admission mortality, and admission were 0.95, 0.98, 0.90, and 0.74, respectively. There were 3 422 865 patients from 2009 who were included for external validation, and the AUCs for predicting mortality in the hospital, the ED, the inpatient ward, and for predicting admission were 0.95, 0.99, 0.90, and 0.75, respectively. Conclusion: The EMR-ESI was notably useful in predicting hospital mortality and the admission of emergency patients.

Original languageEnglish
Pages (from-to)1491-1500
Number of pages10
JournalAmerican Journal of Emergency Medicine
Volume30
Issue number8
DOIs
StatePublished - Oct 2012

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