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VOLUME 21 , ISSUE 12 ( 2017 ) > List of Articles

RESEARCH ARTICLE

Evaluation of quality indicators in an Indian intensive care unit using “CHITRA” database

Kiran Gudivada

Keywords : Benchmark, critically ill, intensive care, quality indicators

Citation Information : Gudivada K. Evaluation of quality indicators in an Indian intensive care unit using “CHITRA” database. Indian J Crit Care Med 2017; 21 (12):841-846.

DOI: 10.4103/ijccm.IJCCM_303_17

License: CC BY-ND 3.0

Published Online: 01-07-2013

Copyright Statement:  Copyright © 2017; The Author(s).


Abstract

Background: Quality indicators (QIs) are essential for maintaining quality of care in the critically ill. The Indian Society of Critical Care Medicine proposed benchmarks and enabled Indian Intensive Care Units (ICUs) to capture data in an electronic database: Customized Health in Intensive Care Trainable Research and Analysis (CHITRA) tool. The purpose of this study is to report QIs in an Indian ICU using this database. Materials and Methods: Data from patients admitted to ICU between October 2015 and January 2017 were entered into CHITRA. The following QIs were analyzed: standardized mortality ratio (SMR), length of ICU stay (LOS-ICU), pressure ulcer (PU) rate, patient fall rate (FR), ICU readmission rate, reintubation rate, ventilator-associated condition (VAC), central line-associated bloodstream infection (CLABSI), catheter-associated urinary tract infection (CAUTI), and iatrogenic pneumothorax rate. Results: A total of 2642 patient's information was suitable for analysis. Median age of ICU admission was 53 years (interquartile range [IQR]: 36–65), with a mean APACHE score of 18 (SD 7.7). Median LOS-ICU was 3 days (IQR 2–6) and SMR was 1.1 (95% confidence interval 1.05–1.38). Pneumothorax rate, PU rate, and FR were 2.6, 4.1, and 0.3 per 1000 respectively, whereas readmission rate was 0.7% and reintubation rate was 3.5%. VAC, CLABSI, and CAUTI were 8.5, 23, 3.1 per 1000 ventilator and catheter days, respectively. Conclusion: This study has successfully evaluated a range of QIs in a mixed ICU of a tertiary hospital utilizing CHITRA database.


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