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提高大型集会健康研究中的数据质量

Improving Data Quality in Mass-Gatherings Health Research.

作者信息

Guy Andrew, Prager Ross, Turris Sheila, Lund Adam

机构信息

1MD Undergraduate Program,University of British Columbia,Vancouver,British Columbia,Canada.

2Department of Emergency Medicine,University of British Columbia,Vancouver,British Columbia,Canada.

出版信息

Prehosp Disaster Med. 2017 Jun;32(3):329-332. doi: 10.1017/S1049023X17000139. Epub 2017 Mar 9.

DOI:10.1017/S1049023X17000139
PMID:28274288
Abstract

Mass gatherings attract large crowds and can strain the planning and health resources of the community, city, or nation hosting an event. Mass-Gatherings Health (MGH) is an evolving niche of prehospital care rooted in emergency medicine, emergency management, public health, and disaster medicine. To explore front-line issues related to data quality in the context of mass gatherings, the authors draw on five years of management experience with an online, mass-gathering event and patient registry, as well as clinical and operational experience amassed over several decades. Here the authors propose underlying human, environmental, and logistical factors that may contribute to poor data quality at mass gatherings, and make specific recommendations for improvement through pre-event planning, on-site actions, and post-event follow-up. The advancement of MGH research will rely on addressing factors that influence data quality and developing strategies to mitigate or enhance those factors. This is an exciting time for MGH research as higher order questions are beginning to be addressed; however, quality research must start from the ground up to ensure optimal primary data capture and quality. Guy A , Prager R , Turris S , Lund A . Improving data quality in mass-gatherings health research. Prehosp Disaster Med. 2017;32(3):329-332.

摘要

大型集会会吸引大量人群,可能会给举办活动的社区、城市或国家的规划和卫生资源带来压力。大型集会卫生(MGH)是院前护理中一个不断发展的细分领域,它植根于急诊医学、应急管理、公共卫生和灾难医学。为了探讨大型集会背景下与数据质量相关的一线问题,作者借鉴了在一个在线大型集会活动和患者登记系统中的五年管理经验,以及几十年来积累的临床和运营经验。在此,作者提出了可能导致大型集会数据质量不佳的潜在人为、环境和后勤因素,并针对活动前规划、现场行动和活动后跟进提出了具体的改进建议。MGH研究的进展将依赖于解决影响数据质量的因素,并制定减轻或增强这些因素的策略。对于MGH研究来说,这是一个令人兴奋的时期,因为更高层次的问题开始得到解决;然而,高质量的研究必须从头开始,以确保最佳的原始数据采集和质量。盖伊A、普拉格R、图里斯S、伦德A。提高大型集会卫生研究中的数据质量。《院前与灾难医学》。2017年;32(3):329 - 332。

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