ArticleScientific reports2023
Influence of social deprivation index on in-hospital outcomes of COVID-19.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Maternal Area of Residence and Outcomes for Mother-Infant Dyads with Perinatal Opioid Exposure.American journal of perinatology · 2026Trial
- Sociodemographic factors that influence COVID-19 healthcare utilization and costs in Alberta, Canada: a population-based study using the Alberta COVID-19 analytics and research database.Frontiers in health services · 2026Article
- Impact of Social Determinants of Health on Outcomes of Nontraumatic Subarachnoid Hemorrhage.Journal of the American Heart Association · 2025Article
- Variation in the time to complete the primary COVID-19 vaccine series by race, ethnicity, and geography among older US adults.Vaccine · 2025Observational
- Evaluating US Multiple Listing Practices in Lung Transplantation: Unveiling Hidden Disparities.Chest · 2024Article
- Telemedicine Disparities in Ambulatory Cardiology Visits in a Large Academic Health System.JACC. Advances · 2024Article
- Realizing the potential of social determinants data in EHR systems: A scoping review of approaches for screening, linkage, extraction, analysis, and interventions.Journal of clinical and translational science · 2024Article
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Authors and funding
12 authors.
Funding
Abstract
While it is known that social deprivation index (SDI) plays an important role on risk for acquiring Coronavirus Disease 2019 (COVID-19), the impact of SDI on in-hospital outcomes such as intubation and mortality are less well-characterized. We analyzed electronic health record data of adults hospitalized with confirmed COVID-19 between March 1, 2020 and February 8, 2021 from the INSIGHT Clinical Research Network (CRN). To compute the SDI (exposure variable), we linked clinical data using patient's residential zip-code with social data at zip-code tabulation area. SDI is a composite of seven socioeconomic characteristics determinants at the zip-code level. For this analysis, we categorized SDI into quintiles. The two outcomes of interest were in-hospital intubation and mortality. For each outcome, we examined logistic regression and random forests to determine incremental value of SDI in predicting outcomes. We studied 30,016 included COVID-19 patients. In a logistic regression model for intubation, a model including demographics, comorbidity, and vitals had an Area under the receiver operating characteristic curve (AUROC) = 0.73 (95% CI 0.70-0.75); the addition of SDI did not improve prediction [AUROC = 0.73 (95% CI 0.71-0.75)]. In a logistic regression model for in-hospital mortality, demographics, comorbidity, and vitals had an AUROC = 0.80 (95% CI 0.79-0.82); the addition of SDI in Model 2 did not improve prediction [AUROC = 0.81 (95% CI 0.79-0.82)]. Random forests revealed similar findings. SDI did not provide incremental improvement in predicting in-hospital intubation or mortality. SDI plays an important role on who acquires COVID-19 and its severity; but once hospitalized, SDI appears less important.
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