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Development and validation of the predictive risk of death model for adult patients admitted to intensive care units in Japan: an approach to improve the accuracy of healthcare quality measures

BACKGROUND: The Acute Physiology and Chronic Health Evaluation (APACHE) III-j model is widely used to predict mortality in Japanese intensive care units (ICUs). Although the model’s discrimination is excellent, its calibration is poor. APACHE III-j overestimates the risk of death, making its evaluat...

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Autores principales: Endo, Hideki, Uchino, Shigehiko, Hashimoto, Satoru, Aoki, Yoshitaka, Hashiba, Eiji, Hatakeyama, Junji, Hayakawa, Katsura, Ichihara, Nao, Irie, Hiromasa, Kawasaki, Tatsuya, Kumasawa, Junji, Kurosawa, Hiroshi, Nakamura, Tomoyuki, Ohbe, Hiroyuki, Okamoto, Hiroshi, Shigemitsu, Hidenobu, Tagami, Takashi, Takaki, Shunsuke, Takimoto, Kohei, Uchida, Masatoshi, Miyata, Hiroaki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885245/
https://www.ncbi.nlm.nih.gov/pubmed/33588956
http://dx.doi.org/10.1186/s40560-021-00533-z
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author Endo, Hideki
Uchino, Shigehiko
Hashimoto, Satoru
Aoki, Yoshitaka
Hashiba, Eiji
Hatakeyama, Junji
Hayakawa, Katsura
Ichihara, Nao
Irie, Hiromasa
Kawasaki, Tatsuya
Kumasawa, Junji
Kurosawa, Hiroshi
Nakamura, Tomoyuki
Ohbe, Hiroyuki
Okamoto, Hiroshi
Shigemitsu, Hidenobu
Tagami, Takashi
Takaki, Shunsuke
Takimoto, Kohei
Uchida, Masatoshi
Miyata, Hiroaki
author_facet Endo, Hideki
Uchino, Shigehiko
Hashimoto, Satoru
Aoki, Yoshitaka
Hashiba, Eiji
Hatakeyama, Junji
Hayakawa, Katsura
Ichihara, Nao
Irie, Hiromasa
Kawasaki, Tatsuya
Kumasawa, Junji
Kurosawa, Hiroshi
Nakamura, Tomoyuki
Ohbe, Hiroyuki
Okamoto, Hiroshi
Shigemitsu, Hidenobu
Tagami, Takashi
Takaki, Shunsuke
Takimoto, Kohei
Uchida, Masatoshi
Miyata, Hiroaki
author_sort Endo, Hideki
collection PubMed
description BACKGROUND: The Acute Physiology and Chronic Health Evaluation (APACHE) III-j model is widely used to predict mortality in Japanese intensive care units (ICUs). Although the model’s discrimination is excellent, its calibration is poor. APACHE III-j overestimates the risk of death, making its evaluation of healthcare quality inaccurate. This study aimed to improve the calibration of the model and develop a Japan Risk of Death (JROD) model for benchmarking purposes. METHODS: A retrospective analysis was conducted using a national clinical registry of ICU patients in Japan. Adult patients admitted to an ICU between April 1, 2018, and March 31, 2019, were included. The APACHE III-j model was recalibrated with the following models: Model 1, predicting mortality with an offset variable for the linear predictor of the APACHE III-j model using a generalized linear model; model 2, predicting mortality with the linear predictor of the APACHE III-j model using a generalized linear model; and model 3, predicting mortality with the linear predictor of the APACHE III-j model using a hierarchical generalized additive model. Model performance was assessed with the area under the receiver operating characteristic curve (AUROC), the Brier score, and the modified Hosmer–Lemeshow test. To confirm model applicability to evaluating quality of care, funnel plots of the standardized mortality ratio and exponentially weighted moving average (EWMA) charts for mortality were drawn. RESULTS: In total, 33,557 patients from 44 ICUs were included in the study population. ICU mortality was 3.8%, and hospital mortality was 8.1%. The AUROC, Brier score, and modified Hosmer–Lemeshow p value of the original model and models 1, 2, and 3 were 0.915, 0.062, and < .001; 0.915, 0.047, and < .001; 0.915, 0.047, and .002; and 0.917, 0.047, and .84, respectively. Except for model 3, the funnel plots showed overdispersion. The validity of the EWMA charts for the recalibrated models was determined by visual inspection. CONCLUSIONS: Model 3 showed good performance and can be adopted as the JROD model for monitoring quality of care in an ICU, although further investigation of the clinical validity of outlier detection is required. This update method may also be useful in other settings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40560-021-00533-z.
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spelling pubmed-78852452021-02-17 Development and validation of the predictive risk of death model for adult patients admitted to intensive care units in Japan: an approach to improve the accuracy of healthcare quality measures Endo, Hideki Uchino, Shigehiko Hashimoto, Satoru Aoki, Yoshitaka Hashiba, Eiji Hatakeyama, Junji Hayakawa, Katsura Ichihara, Nao Irie, Hiromasa Kawasaki, Tatsuya Kumasawa, Junji Kurosawa, Hiroshi Nakamura, Tomoyuki Ohbe, Hiroyuki Okamoto, Hiroshi Shigemitsu, Hidenobu Tagami, Takashi Takaki, Shunsuke Takimoto, Kohei Uchida, Masatoshi Miyata, Hiroaki J Intensive Care Research BACKGROUND: The Acute Physiology and Chronic Health Evaluation (APACHE) III-j model is widely used to predict mortality in Japanese intensive care units (ICUs). Although the model’s discrimination is excellent, its calibration is poor. APACHE III-j overestimates the risk of death, making its evaluation of healthcare quality inaccurate. This study aimed to improve the calibration of the model and develop a Japan Risk of Death (JROD) model for benchmarking purposes. METHODS: A retrospective analysis was conducted using a national clinical registry of ICU patients in Japan. Adult patients admitted to an ICU between April 1, 2018, and March 31, 2019, were included. The APACHE III-j model was recalibrated with the following models: Model 1, predicting mortality with an offset variable for the linear predictor of the APACHE III-j model using a generalized linear model; model 2, predicting mortality with the linear predictor of the APACHE III-j model using a generalized linear model; and model 3, predicting mortality with the linear predictor of the APACHE III-j model using a hierarchical generalized additive model. Model performance was assessed with the area under the receiver operating characteristic curve (AUROC), the Brier score, and the modified Hosmer–Lemeshow test. To confirm model applicability to evaluating quality of care, funnel plots of the standardized mortality ratio and exponentially weighted moving average (EWMA) charts for mortality were drawn. RESULTS: In total, 33,557 patients from 44 ICUs were included in the study population. ICU mortality was 3.8%, and hospital mortality was 8.1%. The AUROC, Brier score, and modified Hosmer–Lemeshow p value of the original model and models 1, 2, and 3 were 0.915, 0.062, and < .001; 0.915, 0.047, and < .001; 0.915, 0.047, and .002; and 0.917, 0.047, and .84, respectively. Except for model 3, the funnel plots showed overdispersion. The validity of the EWMA charts for the recalibrated models was determined by visual inspection. CONCLUSIONS: Model 3 showed good performance and can be adopted as the JROD model for monitoring quality of care in an ICU, although further investigation of the clinical validity of outlier detection is required. This update method may also be useful in other settings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40560-021-00533-z. BioMed Central 2021-02-15 /pmc/articles/PMC7885245/ /pubmed/33588956 http://dx.doi.org/10.1186/s40560-021-00533-z Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Endo, Hideki
Uchino, Shigehiko
Hashimoto, Satoru
Aoki, Yoshitaka
Hashiba, Eiji
Hatakeyama, Junji
Hayakawa, Katsura
Ichihara, Nao
Irie, Hiromasa
Kawasaki, Tatsuya
Kumasawa, Junji
Kurosawa, Hiroshi
Nakamura, Tomoyuki
Ohbe, Hiroyuki
Okamoto, Hiroshi
Shigemitsu, Hidenobu
Tagami, Takashi
Takaki, Shunsuke
Takimoto, Kohei
Uchida, Masatoshi
Miyata, Hiroaki
Development and validation of the predictive risk of death model for adult patients admitted to intensive care units in Japan: an approach to improve the accuracy of healthcare quality measures
title Development and validation of the predictive risk of death model for adult patients admitted to intensive care units in Japan: an approach to improve the accuracy of healthcare quality measures
title_full Development and validation of the predictive risk of death model for adult patients admitted to intensive care units in Japan: an approach to improve the accuracy of healthcare quality measures
title_fullStr Development and validation of the predictive risk of death model for adult patients admitted to intensive care units in Japan: an approach to improve the accuracy of healthcare quality measures
title_full_unstemmed Development and validation of the predictive risk of death model for adult patients admitted to intensive care units in Japan: an approach to improve the accuracy of healthcare quality measures
title_short Development and validation of the predictive risk of death model for adult patients admitted to intensive care units in Japan: an approach to improve the accuracy of healthcare quality measures
title_sort development and validation of the predictive risk of death model for adult patients admitted to intensive care units in japan: an approach to improve the accuracy of healthcare quality measures
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885245/
https://www.ncbi.nlm.nih.gov/pubmed/33588956
http://dx.doi.org/10.1186/s40560-021-00533-z
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