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

• Published in: Journal of clinical and translational science Vol. 7; no. 1; p. e211
• Main Authors: Ma, Jiahui, Johnson, Elizabeth A., McCrory, Bernadette
• Format: Journal Article
• Language: English
• Published: Cambridge Cambridge University Press 01.01.2023
• Subjects: Big Data; clinical trial; Clinical trials; Cross-sectional studies; Datasets; Diagnosis related groups; DRGs; Health care; Health care delivery; healthcare utilization; Hospitals; Information processing; Mortality; Participation; Patients; Pediatrics; Pharmaceutical industry; Research Methods and Technology; Risk factors; safety; Survival; Variables; United States > US
• ISSN: 2059-8661; 2059-8661
• DOI: 10.1017/cts.2023.634

Abstract 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.