Abstract
BACKGROUND: Hand ailments are frequent reasons for emergency department (ED) visits in the United States. This study analyzed the incidence, causes, outcomes, predictors of hospitalization, and healthcare utilization patterns nationwide. METHODS: This retrospective cohort study utilized data from the Nationwide Emergency Department Sample and National Readmission Database from 2016 to 2021. It included patients with a principal diagnosis of hand or wrist complaints. RESULTS: The study included 29,109,534 ED visits for hand ailments. The mean patient age was 36 years. Most patients were Caucasian (61 %), healthy (89 % Charlson Comorbidity score of 0), male (57 %), and from lower income brackets (60 %). Most injuries were unintentional (71 %), with hand lacerations being the most common reason for presentation, followed by closed distal radius fractures. Most patients were discharged home (96 %). Predictors of admission included older age (adjusted odds ratio (aOR) per decade: 1.03; 95 % Confidence Interval (CI): 1.02-1.03; p < 0.01), higher Charlson index (aOR:1.69; CI:1.65-1.73; p < 0.01), Medicaid insurance or uninsured (aOR:1.26; CI:1.18-1.36, aOR:1.25; CI:1.16-1.36; p < 0.01, respectively), and presentation at level I metropolitan trauma teaching hospitals (aOR:3.48; CI:2.98-4.07; p < 0.01). Admission rates increased by 21 % in 2020 compared to 2016. Healthcare expenditure was a staggering $105 billion in total ED and inpatient hospitalization charges. Expenditure increased significantly, surpassing inflation-adjusted rates. CONCLUSIONS: Our analysis of 29 million patients highlights the healthcare burden posed by hand ailments, with lacerations being the most prevalent concern in emergency settings. Admission and readmission rates were influenced by age, comorbidities, socioeconomic status, insurance type, and hospital characteristics. This study provides a basis for targeted interventions in patient outcome enhancement and resource allocation. Limitations include the reliance on ICD-10-CM coding in the absence of clinical data, which may impact the accuracy of case identification and classification.