Toward trustworthy medical device in silico clinical trials: a hierarchical framework for establishing credibility and strategies for overcoming key challenges
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ABSTRACT:
SUBMITTER: Aycock K
PROVIDER: S-EPMC11346031 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:IntroductionComprehensive identification of out-of-hospital cardiac arrest (OHCA) cases for inclusion in registries remains challenging due to the inherent diversity of OHCA aetiology, presentation, and management. The Northern Adelaide Local Health Network (NALHN) OHCA registry identifies OHCAs presenting to NALHN hospitals using existing data sources to monitor in-hospital treatment and survival. This study aimed to investigate the accuracy of hospital-based data sources for identifying OHCA cases treated at hospital.MethodsRetrospective analysis of all OHCAs aged >18 years included in the NALHN OHCA registry between 2011-16. Registry cases are identified from an emergency medical service (EMS) OHCA registry, Emergency Department (ED) and ICD-10 coding datasets, and key-word searches of two in-hospital clinical registries. Sensitivity and positive predictive values (PPV) of each hospital-based data source were analysed with respect to (a) the number of cases expected to be identified by that source, (b) total OHCA. Non-OHCAs yielded by each source were explored and a sub-analysis of ICD-10 codes was performed.ResultsBetween 2011-16, the four hospital-based sources yielded 992 cases, of which 383 were confirmed as OHCA. The ED coding dataset was the most accurate with a sensitivity and PPV of 78%. The ICD-10 coding dataset had good sensitivity but low PPV (33%). The ED coding dataset, combined with the two in-hospital clinical registries, identified 93% of OHCAs.ConclusionsNo single dataset identified all OHCAs presenting to NALHN hospitals. Combined hospital-based data sources provide a valid method of identifying OHCAs treated at hospital that may be adapted to augment EMS-based data.
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