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Predicting risk factors for pediatric mortality in clinical trial research: A retrospective, cross-sectional study using a Healthcare Cost and Utilization Project database

INTRODUCTION: Incorporating real-world data using “big data” analysis in healthcare are useful to extract specific information for healthcare delivery system improvement. All-cause mortality is an essential measure to enhance patient safety in clinical trial research, especially for underrepresented...

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Autores principales: Ma, Jiahui, Johnson, Elizabeth A., McCrory, Bernadette
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10603364/
https://www.ncbi.nlm.nih.gov/pubmed/37900356
http://dx.doi.org/10.1017/cts.2023.634
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author Ma, Jiahui
Johnson, Elizabeth A.
McCrory, Bernadette
author_facet Ma, Jiahui
Johnson, Elizabeth A.
McCrory, Bernadette
author_sort Ma, Jiahui
collection PubMed
description INTRODUCTION: Incorporating real-world data using “big data” analysis in healthcare are useful to extract specific information for healthcare delivery system improvement. All-cause mortality is an essential measure to enhance patient safety in clinical trial research, especially for underrepresented pediatric participants. OBJECTIVE: This study aimed to determine the associations between pediatric mortality and patient-specific factors using the Healthcare Cost and Utilization Project (HCUP) database. METHODS: Data from the 2019 the HCUP Kids’ Inpatient Database (KID) were used to conduct a logistic regression analysis to determine associations between pediatric patients’ the chance of survival and their demographic and socioeconomic background, discharge records, and hospital information. RESULTS: Total number of diagnoses (OR = 0.84), total number of procedures (OR = 0.86), length of stay (OR = 1.04), age intervals greater than 1 year (OR > 1.0), transfer into the hospital from a different acute care (OR = 0.34), major diagnoses of multiple significant trauma (OR = 0.03) or hepatobiliary system and pancreas (OR = 0.10), region of hospital – west and midwest (OR > 1.0), and medium or larger hospital bed size (OR > 1.0) were all significantly associated with the chance of survival for patients participating in pediatric clinical trials (p < 0.05). CONCLUSION: Real-world clinical trial data analysis showed the potential improvement area including reallocating trial resources to promote trial quality and safe participation for pediatric patients. Pediatric trials need tools that are developed using user-centered design approaches to satisfy the unique needs and requirements of pediatric patients and their caregivers. Safe intrahospital transfer procedures and active dissemination of successful trial best practices are crucial to trial management, adherence, quality, and safety.
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spelling pubmed-106033642023-10-28 Predicting risk factors for pediatric mortality in clinical trial research: A retrospective, cross-sectional study using a Healthcare Cost and Utilization Project database Ma, Jiahui Johnson, Elizabeth A. McCrory, Bernadette J Clin Transl Sci Research Article INTRODUCTION: Incorporating real-world data using “big data” analysis in healthcare are useful to extract specific information for healthcare delivery system improvement. All-cause mortality is an essential measure to enhance patient safety in clinical trial research, especially for underrepresented pediatric participants. OBJECTIVE: This study aimed to determine the associations between pediatric mortality and patient-specific factors using the Healthcare Cost and Utilization Project (HCUP) database. METHODS: Data from the 2019 the HCUP Kids’ Inpatient Database (KID) were used to conduct a logistic regression analysis to determine associations between pediatric patients’ the chance of survival and their demographic and socioeconomic background, discharge records, and hospital information. RESULTS: Total number of diagnoses (OR = 0.84), total number of procedures (OR = 0.86), length of stay (OR = 1.04), age intervals greater than 1 year (OR > 1.0), transfer into the hospital from a different acute care (OR = 0.34), major diagnoses of multiple significant trauma (OR = 0.03) or hepatobiliary system and pancreas (OR = 0.10), region of hospital – west and midwest (OR > 1.0), and medium or larger hospital bed size (OR > 1.0) were all significantly associated with the chance of survival for patients participating in pediatric clinical trials (p < 0.05). CONCLUSION: Real-world clinical trial data analysis showed the potential improvement area including reallocating trial resources to promote trial quality and safe participation for pediatric patients. Pediatric trials need tools that are developed using user-centered design approaches to satisfy the unique needs and requirements of pediatric patients and their caregivers. Safe intrahospital transfer procedures and active dissemination of successful trial best practices are crucial to trial management, adherence, quality, and safety. Cambridge University Press 2023-09-22 /pmc/articles/PMC10603364/ /pubmed/37900356 http://dx.doi.org/10.1017/cts.2023.634 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
spellingShingle Research Article
Ma, Jiahui
Johnson, Elizabeth A.
McCrory, Bernadette
Predicting risk factors for pediatric mortality in clinical trial research: A retrospective, cross-sectional study using a Healthcare Cost and Utilization Project database
title Predicting risk factors for pediatric mortality in clinical trial research: A retrospective, cross-sectional study using a Healthcare Cost and Utilization Project database
title_full Predicting risk factors for pediatric mortality in clinical trial research: A retrospective, cross-sectional study using a Healthcare Cost and Utilization Project database
title_fullStr Predicting risk factors for pediatric mortality in clinical trial research: A retrospective, cross-sectional study using a Healthcare Cost and Utilization Project database
title_full_unstemmed Predicting risk factors for pediatric mortality in clinical trial research: A retrospective, cross-sectional study using a Healthcare Cost and Utilization Project database
title_short Predicting risk factors for pediatric mortality in clinical trial research: A retrospective, cross-sectional study using a Healthcare Cost and Utilization Project database
title_sort predicting risk factors for pediatric mortality in clinical trial research: a retrospective, cross-sectional study using a healthcare cost and utilization project database
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10603364/
https://www.ncbi.nlm.nih.gov/pubmed/37900356
http://dx.doi.org/10.1017/cts.2023.634
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