Incidence and characteristics of fall-related emergency department visits
Abstract
OBJECTIVE: Unintentional falls are the leading cause of injury and the second most common cause of unintentional injury deaths in the United States, and place a great burden on EDs. In this study, the objective was to describe the incidence and characteristics of ED visits associated with unintentional falls in the United States.
METHODS: The authors performed a secondary analysis on data from the National Center for Health Statistics' National Hospital Ambulatory Medical Care Survey for 1992-1994. An ED visit was defined as fall-related if an ICD-9-CM cause of injury code was reported as E880.0-886.9 or E888.
RESULTS: There were an estimated 7,946,000 fall-related ED visits per year, corresponding to an annual rate of 3.1 per 100 persons (95% CI=2.8 to 3.4). Children under 5 years of age comprised the largest proportion of visits (14%). Among those visits coded with respect to place of occurrence, the rate of visits associated with falls occurring at home (1.7/100; 95% CI=1.6 to 1.9) was significantly higher than that associated with falls occurring in all other locations combined (1.1/100; 95% CI=1.0 to 1.2). The mean injury severity score increased significantly with the age of the patient. Fall-related ED visits resulted in an estimated 860,000 hospitalizations, 62% of which involved individuals aged 65 years and older. An estimated $2.45 billion per year was paid for fall-related ED visits. Government sources paid all or part of 41% of visits.
CONCLUSIONS: This study…
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.