Wittwer Melanie R, Ruknuddeen Mohammed Ishaq, Thorrowgood Mel, Zeitz Chris, Beltrame John F, Arstall Margaret A
University of Adelaide, Adelaide, South Australia, Australia.
Northern Adelaide Local Health Network, Elizabeth Vale, South Australia, Australia.
Resusc Plus. 2021 May 16;6:100136. doi: 10.1016/j.resplu.2021.100136. eCollection 2021 Jun.
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.
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.
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.
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.
由于院外心脏骤停(OHCA)的病因、表现和处理存在内在多样性,全面识别纳入登记系统的院外心脏骤停病例仍然具有挑战性。北阿德莱德地方卫生网络(NALHN)的院外心脏骤停登记系统利用现有数据源识别送往NALHN医院的院外心脏骤停病例,以监测院内治疗和生存情况。本研究旨在调查基于医院的数据源识别在医院接受治疗的院外心脏骤停病例的准确性。
对2011年至2016年间纳入NALHN院外心脏骤停登记系统的所有18岁以上院外心脏骤停病例进行回顾性分析。登记病例从紧急医疗服务(EMS)院外心脏骤停登记系统、急诊科(ED)和国际疾病分类第10版(ICD-10)编码数据集以及两个院内临床登记系统的关键词搜索中识别出来。分析每个基于医院的数据源相对于(a)该数据源预期识别的病例数、(b)院外心脏骤停总数的敏感性和阳性预测值(PPV)。探索每个数据源产生的非院外心脏骤停病例,并对ICD-10编码进行亚分析。
2011年至2016年间,四个基于医院的数据源产生了992例病例,其中383例被确认为院外心脏骤停。急诊科编码数据集最准确,敏感性和PPV为78%。ICD-10编码数据集敏感性良好,但PPV较低(33%)。急诊科编码数据集与两个院内临床登记系统相结合,识别出93%的院外心脏骤停病例。
没有单一数据集能识别送往NALHN医院的所有院外心脏骤停病例。基于医院的综合数据源提供了一种识别在医院接受治疗的院外心脏骤停病例的有效方法,可用于补充基于紧急医疗服务的数据。