The Korean journal of internal medicine

The Korean Association of Internal Medicine (대한내과학회)
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Development and validation of novel simple prognostic model for predicting mortality in Korean intensive care units using national insurance claims data

  • Ah Young Leem (Division of Pulmonology, Department of Internal Medicine, Institute of Chest Disease, Severance Hospital, Yonsei University College of Medicine) ;
  • Soyul Han (Department of Statistics, Graduate School of Chung-Ang University) ;
  • Kyung Soo Chung (Division of Pulmonology, Department of Internal Medicine, Institute of Chest Disease, Severance Hospital, Yonsei University College of Medicine) ;
  • Su Hwan Lee (Division of Pulmonology, Department of Internal Medicine, Institute of Chest Disease, Severance Hospital, Yonsei University College of Medicine) ;
  • Moo Suk Park (Division of Pulmonology, Department of Internal Medicine, Institute of Chest Disease, Severance Hospital, Yonsei University College of Medicine) ;
  • Bora Lee (Institute of Health & Environment, Seoul National University) ;
  • Young Sam Kim (Division of Pulmonology, Department of Internal Medicine, Institute of Chest Disease, Severance Hospital, Yonsei University College of Medicine)
  • Received : 2022.10.07
  • Accepted : 2023.11.27
  • Published : 2024.07.01
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Abstract

Background/Aims: Intensive care unit (ICU) quality is largely determined by the mortality rate. Therefore, we aimed to develop and validate a novel prognostic model for predicting mortality in Korean ICUs, using national insurance claims data. Methods: Data were obtained from the health insurance claims database maintained by the Health Insurance Review and Assessment Service of South Korea. From patients who underwent the third ICU adequacy evaluation, 42,489 cases were enrolled and randomly divided into the derivation and validation cohorts. Using the models derived from the derivation cohort, we analyzed whether they accurately predicted death in the validation cohort. The models were verified using data from one general and two tertiary hospitals. Results: Two severity correction models were created from the derivation cohort data, by applying variables selected through statistical analysis, through clinical consensus, and from performing multiple logistic regression analysis. Model 1 included six categorical variables (age, sex, Charlson comorbidity index, ventilator use, hemodialysis or continuous renal replacement therapy, and vasopressor use). Model 2 additionally included presence/absence of ICU specialists and nursing grades. In external validation, the performance of models 1 and 2 for predicting in-hospital and ICU mortality was not inferior to that of pre-existing scoring systems. Conclusions: The novel and simple models could predict in-hospital and ICU mortality and were not inferior compared to the pre-existing scoring systems.

Keywords

Acknowledgement

This work was supported by the Health Insurance Review & Assessment Service (HIRA). The views expressed are those of the author(s) and not necessarily those of the HIRA.

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