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Evaluation of ICUs and weight of quality control indicators: an exploratory study based on Chinese ICU quality data from 2015 to 2020

This study aimed to explore key quality control factors that affected the prognosis of intensive care unit (ICU) patients in Chinese mainland over six years (2015–2020). The data for this study were from 31 provincial and municipal hospitals (3425 hospital ICUs) and included 2 110 685 ICU patients,...

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Autores principales: Su, Longxiang, Ma, Xudong, Gao, Sifa, Yin, Zhi, Chen, Yujie, Wang, Wenhu, He, Huaiwu, Du, Wei, Hu, Yaoda, Ma, Dandan, Zhang, Feng, Zhu, Wen, Meng, Xiaoyang, Sun, Guoqiang, Ma, Lian, Jiang, Huizhen, Shan, Guangliang, Liu, Dawei, Zhou, Xiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Higher Education Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10105137/
https://www.ncbi.nlm.nih.gov/pubmed/37060524
http://dx.doi.org/10.1007/s11684-022-0970-x
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author Su, Longxiang
Ma, Xudong
Gao, Sifa
Yin, Zhi
Chen, Yujie
Wang, Wenhu
He, Huaiwu
Du, Wei
Hu, Yaoda
Ma, Dandan
Zhang, Feng
Zhu, Wen
Meng, Xiaoyang
Sun, Guoqiang
Ma, Lian
Jiang, Huizhen
Shan, Guangliang
Liu, Dawei
Zhou, Xiang
author_facet Su, Longxiang
Ma, Xudong
Gao, Sifa
Yin, Zhi
Chen, Yujie
Wang, Wenhu
He, Huaiwu
Du, Wei
Hu, Yaoda
Ma, Dandan
Zhang, Feng
Zhu, Wen
Meng, Xiaoyang
Sun, Guoqiang
Ma, Lian
Jiang, Huizhen
Shan, Guangliang
Liu, Dawei
Zhou, Xiang
author_sort Su, Longxiang
collection PubMed
description This study aimed to explore key quality control factors that affected the prognosis of intensive care unit (ICU) patients in Chinese mainland over six years (2015–2020). The data for this study were from 31 provincial and municipal hospitals (3425 hospital ICUs) and included 2 110 685 ICU patients, for a total of 27 607 376 ICU hospitalization days. We found that 15 initially established quality control indicators were good predictors of patient prognosis, including percentage of ICU patients out of all inpatients (%), percentage of ICU bed occupancy of total inpatient bed occupancy (%), percentage of all ICU inpatients with an APACHE II score ⩾15 (%), three-hour (surviving sepsis campaign) SSC bundle compliance (%), six-hour SSC bundle compliance (%), rate of microbe detection before antibiotics (%), percentage of drug deep venous thrombosis (DVT) prophylaxis (%), percentage of unplanned endotracheal extubations (%), percentage of patients reintubated within 48 hours (%), unplanned transfers to the ICU (%), 48-h ICU readmission rate (%), ventilator associated pneumonia (VAP) (per 1000 ventilator days), catheter related blood stream infection (CRBSI) (per 1000 catheter days), catheter-associated urinary tract infections (CAUTI) (per 1000 catheter days), in-hospital mortality (%). When exploratory factor analysis was applied, the 15 indicators were divided into 6 core elements that varied in weight regarding quality evaluation: nosocomial infection management (21.35%), compliance with the Surviving Sepsis Campaign guidelines (17.97%), ICU resources (17.46%), airway management (15.53%), prevention of deep-vein thrombosis (14.07%), and severity of patient condition (13.61%). Based on the different weights of the core elements associated with the 15 indicators, we developed an integrated quality scoring system defined as F score=21.35%xnosocomial infection management + 17.97%xcompliance with SSC guidelines + 17.46%×ICU resources + 15.53%×airway management + 14.07%×DVT prevention + 13.61%×severity of patient condition. This evidence-based quality scoring system will help in assessing the key elements of quality management and establish a foundation for further optimization of the quality control indicator system.
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spelling pubmed-101051372023-04-17 Evaluation of ICUs and weight of quality control indicators: an exploratory study based on Chinese ICU quality data from 2015 to 2020 Su, Longxiang Ma, Xudong Gao, Sifa Yin, Zhi Chen, Yujie Wang, Wenhu He, Huaiwu Du, Wei Hu, Yaoda Ma, Dandan Zhang, Feng Zhu, Wen Meng, Xiaoyang Sun, Guoqiang Ma, Lian Jiang, Huizhen Shan, Guangliang Liu, Dawei Zhou, Xiang Front Med Research Article This study aimed to explore key quality control factors that affected the prognosis of intensive care unit (ICU) patients in Chinese mainland over six years (2015–2020). The data for this study were from 31 provincial and municipal hospitals (3425 hospital ICUs) and included 2 110 685 ICU patients, for a total of 27 607 376 ICU hospitalization days. We found that 15 initially established quality control indicators were good predictors of patient prognosis, including percentage of ICU patients out of all inpatients (%), percentage of ICU bed occupancy of total inpatient bed occupancy (%), percentage of all ICU inpatients with an APACHE II score ⩾15 (%), three-hour (surviving sepsis campaign) SSC bundle compliance (%), six-hour SSC bundle compliance (%), rate of microbe detection before antibiotics (%), percentage of drug deep venous thrombosis (DVT) prophylaxis (%), percentage of unplanned endotracheal extubations (%), percentage of patients reintubated within 48 hours (%), unplanned transfers to the ICU (%), 48-h ICU readmission rate (%), ventilator associated pneumonia (VAP) (per 1000 ventilator days), catheter related blood stream infection (CRBSI) (per 1000 catheter days), catheter-associated urinary tract infections (CAUTI) (per 1000 catheter days), in-hospital mortality (%). When exploratory factor analysis was applied, the 15 indicators were divided into 6 core elements that varied in weight regarding quality evaluation: nosocomial infection management (21.35%), compliance with the Surviving Sepsis Campaign guidelines (17.97%), ICU resources (17.46%), airway management (15.53%), prevention of deep-vein thrombosis (14.07%), and severity of patient condition (13.61%). Based on the different weights of the core elements associated with the 15 indicators, we developed an integrated quality scoring system defined as F score=21.35%xnosocomial infection management + 17.97%xcompliance with SSC guidelines + 17.46%×ICU resources + 15.53%×airway management + 14.07%×DVT prevention + 13.61%×severity of patient condition. This evidence-based quality scoring system will help in assessing the key elements of quality management and establish a foundation for further optimization of the quality control indicator system. Higher Education Press 2023-04-15 /pmc/articles/PMC10105137/ /pubmed/37060524 http://dx.doi.org/10.1007/s11684-022-0970-x Text en © Higher Education Press 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Research Article
Su, Longxiang
Ma, Xudong
Gao, Sifa
Yin, Zhi
Chen, Yujie
Wang, Wenhu
He, Huaiwu
Du, Wei
Hu, Yaoda
Ma, Dandan
Zhang, Feng
Zhu, Wen
Meng, Xiaoyang
Sun, Guoqiang
Ma, Lian
Jiang, Huizhen
Shan, Guangliang
Liu, Dawei
Zhou, Xiang
Evaluation of ICUs and weight of quality control indicators: an exploratory study based on Chinese ICU quality data from 2015 to 2020
title Evaluation of ICUs and weight of quality control indicators: an exploratory study based on Chinese ICU quality data from 2015 to 2020
title_full Evaluation of ICUs and weight of quality control indicators: an exploratory study based on Chinese ICU quality data from 2015 to 2020
title_fullStr Evaluation of ICUs and weight of quality control indicators: an exploratory study based on Chinese ICU quality data from 2015 to 2020
title_full_unstemmed Evaluation of ICUs and weight of quality control indicators: an exploratory study based on Chinese ICU quality data from 2015 to 2020
title_short Evaluation of ICUs and weight of quality control indicators: an exploratory study based on Chinese ICU quality data from 2015 to 2020
title_sort evaluation of icus and weight of quality control indicators: an exploratory study based on chinese icu quality data from 2015 to 2020
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10105137/
https://www.ncbi.nlm.nih.gov/pubmed/37060524
http://dx.doi.org/10.1007/s11684-022-0970-x
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