Harnessing Routinely Collected Health Data for Global Monitoring of Stroke: Roadmap and Vision for INSPIRE-STROKE.

IF 4 3区 医学 Q2 CLINICAL NEUROLOGY
Lachlan L Dalli, Muideen T Olaiya, Amy Y X Yu, Mathew J Reeves, Dominique A Cadilhac, Lee Nedkoff, Valery Feigin, Bo Norrving, Moira K Kapral, William Whiteley, Anne-Marie Schott, Julia Ferrari, Hanne Christensen, Brian Mac Grory, Eric E Smith, Yannick Béjot, Manav Vyas, Nishant K Mishra, Jong-Moo Park, Michael D Hill, Christine Benne-Christensent, Seana L Gall, Monique F Kilkenny
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引用次数: 0

Abstract

Introduction: Sustainable and low-cost data systems for national and global surveillance of stroke are urgently needed to address the growing burden of stroke. Routinely collected health data (including registries and administrative data) are proliferating at a rapid pace, offering promise for systematic and enduring global stroke surveillance. However, several challenges exist in utilising these routinely collected data from across the globe for global stroke surveillance, such as non-standardised definitions and coding, missingness of data, and lack of transparent or reproducible methods. We aim to describe the vision and methods for a new global collaboration to leverage and harmonise population-level health data for global stroke surveillance.

Methods: The International Network for Standardised Population Insights and Real-world Evidence for STROKE (INSPIRE-STROKE) was established in October 2023 and currently includes 39 collaborators from 16 countries. The vision of INSPIRE-STROKE is to develop new methods that will harmonise and combine health databases across the world to facilitate reliable and robust multi-country stroke surveillance. Through this scientific community, we are initially collaborating to 1) summarise existing methods for calculating and reporting measures of post-stroke outcomes using routinely collected health data; 2) develop consensus-based standards for analysing routinely collected health data on post-stroke outcomes; and 3) conduct proof-of-concept studies to align variables/definitions in routinely collected health data and create standardised statistical code to measure post-stroke outcomes (e.g., medication adherence, readmissions, and mortality) according to consensus-based definitions.

Conclusion: INSPIRE-STROKE will support more reliable investigations into country-level trends in stroke incidence and outcomes, by leveraging routinely collected health data at a global scale. The large and diverse data compiled for INSPIRE-STROKE could facilitate exploration of rare stroke outcomes, particularly among under-represented groups (e.g., pregnant women, children). INSPIRE-STROKE will strengthen health policy and resource planning by providing high-quality evidence to improve access to stroke care and maximise patient outcomes.

利用常规收集的健康数据进行中风的全球监测:INSPIRE-STROKE的路线图和愿景。
为解决日益增长的中风负担,迫切需要用于国家和全球卒中监测的可持续和低成本数据系统。常规收集的健康数据(包括登记和行政数据)正在迅速增加,为系统和持久的全球卒中监测提供了希望。然而,在利用这些从全球各地常规收集的数据进行全球脑卒中监测方面存在一些挑战,如非标准化的定义和编码、数据缺失以及缺乏透明或可重复的方法。我们的目标是描述一种新的全球合作的愿景和方法,以利用和协调全球卒中监测的人口水平的健康数据。方法:卒中标准化人群洞察和现实世界证据国际网络(INSPIRE-STROKE)成立于2023年10月,目前包括来自16个国家的39位合作者。INSPIRE-STROKE的愿景是开发新的方法,协调和结合世界各地的卫生数据库,促进可靠和强大的多国卒中监测。通过这个科学团体,我们最初的合作是:1)总结现有的方法,利用常规收集的健康数据来计算和报告中风后的结果;2)制定基于共识的标准,用于分析常规收集的关于卒中后结局的健康数据;3)开展概念验证研究,以调整常规收集的健康数据中的变量/定义,并根据基于共识的定义创建标准化统计代码,以衡量中风后的结果(例如,药物依从性、再入院率和死亡率)。结论:INSPIRE-STROKE将通过利用全球范围内常规收集的健康数据,支持对卒中发病率和预后的国家级趋势进行更可靠的调查。为INSPIRE-STROKE收集的大量多样的数据有助于探索罕见的中风结果,特别是在代表性不足的群体(如孕妇、儿童)中。INSPIRE-STROKE将通过提供高质量的证据来改善卒中治疗的可及性并最大限度地提高患者的治疗效果,从而加强卫生政策和资源规划。
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来源期刊
Neuroepidemiology
Neuroepidemiology 医学-公共卫生、环境卫生与职业卫生
CiteScore
9.90
自引率
1.80%
发文量
49
审稿时长
6-12 weeks
期刊介绍: ''Neuroepidemiology'' is the only internationally recognised peer-reviewed periodical devoted to descriptive, analytical and experimental studies in the epidemiology of neurologic disease. The scope of the journal expands the boundaries of traditional clinical neurology by providing new insights regarding the etiology, determinants, distribution, management and prevention of diseases of the nervous system.
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