Screening for Health-Related Social Needs of Emergency Department Patients
Abstract
STUDY OBJECTIVE: There has been increasing attention to screening for health-related social needs. However, little is known about the screening practices of emergency departments (EDs). Within New England, we seek to identify the prevalence of ED screening for health-related social needs, understand the factors associated with screening, and understand how screening patterns for health-related social needs differ from those for violence, substance use, and mental health needs.
METHODS: We analyzed data from the 2018 National Emergency Department Inventory-New England survey, which was administered to all 194 New England EDs during 2019. We used descriptive statistics to compare ED characteristics by screening practices, and multivariable logistic regression models to identify factors associated with screening.
RESULTS: Among the 166 (86%) responding EDs, 64 (39%) reported screening for at least one health-related social need, 160 (96%) for violence (including intimate partner violence or other violent exposures), 148 (89%) for substance use disorder, and 159 (96%) for mental health needs. EDs reported a wide range of social work resources to address identified needs, with 155 (93%) reporting any social worker availability and 41 (27%) reporting continuous availability.
CONCLUSION: New England EDs are screening for health-related social needs at a markedly lower rate than for violence, substance use, and mental health needs. EDs have relatively limited resources available to…
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.