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Accurate determinations of the time of intubation (TOI) are critical for retrospective electronic health record (EHR) data analyses. In a retrospective study, the authors developed and validated an improved query (Ti) to identify TOI across numerous settings in a large health system, using EHR data, during the COVID-19 pandemic. Further, they evaluated the affect of Ti on peri-intubation patient parameters compared to a previous method-ventilator parameters (Tv). Ti identified an earlier TOI for 84.8% (n = 1666) of cases with a mean (SD) of 3.5 hours (15.5), resulting in alternate values for: partial pressure of arterial oxygen (PaO 2 ) in 18.4% of patients (mean 43.95 mmHg [54.24]); PaO 2 /fractional inspired oxygen (FiO 2 ) in 17.8% of patients (mean 48.29 [69.81]), and oxygen saturation/FiO 2 in 62.7% (mean 16.75 [34.14]), using the absolute difference in mean values within the first 4 hours of intubation. Differences in PaO 2 /FiO 2 using Ti versus Tv resulted in the reclassification of 7.3% of patients into different acute respiratory distress syndrome (ARDS) severity categories.
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http://dx.doi.org/10.1097/JMQ.0000000000000048 | DOI Listing |
BMJ Open
September 2025
Department of Epidemiology, School of Public Health, and Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China
Objectives: Although lung cancer in never smokers (LCNSs) accounts for an estimated 25% of all lung cancer cases, the temporal trends in LCNS incidence and its broader epidemiological patterns remain poorly understood. Our study examines the temporal trends in LCNS incidence and analyses key epidemiological characteristics, specifically, the trends in mortality rates, survival rates and changes in age at onset to illuminate the reasons for temporal trends in LCNS incidence.
Design: Retrospective population-based cohort study.
Appl Clin Inform
September 2025
Pediatric Critical Care, Stanford University School of Medicine, Stanford, United States.
Background: Time spent in the electronic health record (EHR) is an important measure of clinical activity. Vendor-derived EHR use metrics may not correspond to actual EHR experience. Raw EHR audit logs enable customized EHR use metrics, but translating discrete timestamps to time intervals is challenging.
View Article and Find Full Text PDFJMIR Cancer
September 2025
iCARE Secure Data Environment & Digital Collaboration Space, NIHR Imperial Biomedical Research Centre, London, United Kingdom.
Background: Electronic health records (EHRs) are a cornerstone of modern health care delivery, but their current configuration often fragments information across systems, impeding timely and effective clinical decision-making. In gynecological oncology, where care involves complex, multidisciplinary coordination, these limitations can significantly impact the quality and efficiency of patient management. Few studies have examined how EHR systems support clinical decision-making from the perspective of end users.
View Article and Find Full Text PDFJMIR Med Inform
September 2025
College of Medical Informatics, Chongqing Medical University, 1 Yixueyuan Road, Yuzhong District, Chongqing, 400016, China, 86 13500303273.
Background: Cirrhosis is a leading cause of noncancer deaths in gastrointestinal diseases, resulting in high hospitalization and readmission rates. Early identification of high-risk patients is vital for proactive interventions and improving health care outcomes. However, the quality and integrity of real-world electronic health records (EHRs) limit their utility in developing risk assessment tools.
View Article and Find Full Text PDFPLoS One
September 2025
Center of Innovation and Value, Parkland Health, Dallas, Texas, United States of America.
Purpose: Decreased access to care and social drivers of health have been implicated in COVID-19 disparities. The objective of this study was to test the association between county-funded charity coverage (CFCC) and mortality among uninsured patients hospitalized with COVID-19 in a highly uninsured county.
Methods: This retrospective cohort study compared electronic health record (EHR) data among uninsured patients hospitalized with COVID-19 in a high-volume safety-net health system in Dallas County, Texas between June 2020 and December 2021.