Overcoming challenges of establishing a hospital-based out-of-hospital cardiac arrest registry: accuracy of case identification using administrative data and clinical registries

Resuscitation Plus

卷:6

Mel Thorrowgood¹  Mohammed Ishaq Ruknuddeen²  John F. Beltrame²  Margaret A. Arstall³  Melanie R. Wittwer⁴  Chris Zeitz⁴ 

[1] Corresponding author at: University of Adelaide, Northern Adelaide Local Health Network, Clinical Trials Unit, Lyell McEwin Hospital, Haydown Road, Elizabeth Vale, SA, 5112, Australia.;

[2] Northern Adelaide Local Health Network, Elizabeth Vale, South Australia, Australia;

[3] SA Ambulance Service, Eastwood, South Australia, Australia;

[4] University of Adelaide, Adelaide, South Australia, Australia;

关键词: Out-of-hospital cardiac arrest;    Registry;    ICD-10;    Administrative data;    Utstein template;    Validation;   

DOI  :  

来源: DOAJ

【 摘 要 】

Introduction: Comprehensive 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. Methods: Retrospective 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. Results: Between 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. Conclusions: No 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.

【 授权许可】

Unknown