Liberman Danica B, Tam Jonathan S, Cushing Anna M, Espinoza Juan
Division of Emergency and Transport Medicine Children's Hospital Los Angeles Los Angeles California USA.
Department of Pediatrics, Keck School of Medicine University of Southern California Los Angeles California USA.
J Am Coll Emerg Physicians Open. 2024 Aug 14;5(4):e13240. doi: 10.1002/emp2.13240. eCollection 2024 Aug.
Asthma, the most common chronic disease in children, affects more than 4 million children in the United States, disproportionately affecting those who are economically disadvantaged and racial and ethnic minorities. Studies have shown that the racial and ethnic disparities in asthma outcomes can be largely explained by environmental, socioeconomic and other social determinants of health (SDoH). Utilizing new approaches to stratify disease severity and risk, which focus on the underlying SDoH that lead to asthma disparity, provides an opportunity to disentangle race and ethnicity from its confounding social determinants. In particular, with the growing use of geospatial information systems, geocoded data can enable researchers and clinicians to quantify social and environmental impacts of structural racism. When these data are systematically collected and tabulated, researchers, and ultimately clinicians at the bedside, can evaluate patients' neighborhood context and create targeted interventions toward those factors most associated with asthma morbidity. To do this, we have designed a view (mPage in the Cerner electronic health record) that centralizes key clinical information and displays it alongside SDoH variables shown to be linked to asthma incidence and severity. Once refined and validated, which is the next step in our project, our goal is for emergency medicine clinicians to use these data in real time while caring for patients with asthma. Our multidisciplinary, patient-centered approach that leverages modern informatics tools will create opportunities to better triage patients with asthma exacerbations, choose the best interventions, and target underlying determinants of disease.
哮喘是儿童中最常见的慢性疾病,在美国影响着超过400万儿童,对经济上处于不利地位以及种族和少数民族的儿童影响尤为严重。研究表明,哮喘治疗结果中的种族和民族差异在很大程度上可由环境、社会经济和其他健康的社会决定因素(SDoH)来解释。采用新方法对疾病严重程度和风险进行分层,重点关注导致哮喘差异的潜在SDoH,为将种族和民族与其混杂的社会决定因素区分开来提供了机会。特别是,随着地理空间信息系统的日益普及,地理编码数据能够使研究人员和临床医生量化结构性种族主义的社会和环境影响。当这些数据被系统地收集和制表后,研究人员以及最终床边的临床医生能够评估患者的邻里环境,并针对那些与哮喘发病率最相关的因素制定有针对性的干预措施。为此,我们设计了一个视图(Cerner电子健康记录中的mPage),该视图集中了关键临床信息,并将其与显示与哮喘发病率和严重程度相关的SDoH变量一起展示。一旦完善并验证,这是我们项目的下一步,我们的目标是让急诊医学临床医生在护理哮喘患者时实时使用这些数据。我们以患者为中心的多学科方法利用现代信息学工具,将创造机会更好地对哮喘急性加重患者进行分诊,选择最佳干预措施,并针对疾病的潜在决定因素。