Danica B. Liberman MD, MPH, Jonathan S. Tam MD, Anna M. Cushing MD, Juan Espinoza MD
{"title":"A novel tool using social and environmental determinants of health to assess pediatric asthma in the emergency department","authors":"Danica B. Liberman MD, MPH, Jonathan S. Tam MD, Anna M. Cushing MD, Juan Espinoza MD","doi":"10.1002/emp2.13240","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":73967,"journal":{"name":"Journal of the American College of Emergency Physicians open","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/emp2.13240","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American College of Emergency Physicians open","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/emp2.13240","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"EMERGENCY MEDICINE","Score":null,"Total":0}
引用次数: 0
Abstract
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.