Study reveals high rates of opioid and antibiotic prescriptions in dental pain cases at emergency departments, implying a need for better prescribing practices.
Overprescription of opioids and antibiotics remains a significant public health challenge in the US, contributing to systemic and dental health issues. This study developed and tested a natural language processing (NLP) model to identify patients visiting the emergency department (ED) at Temple University Health System for dental-related reasons. We extracted data from EHR and EDR systems, yielding a cohort of 89,349 patients, including 2,918 (3%) with dental-related ED visits. Using gold-standard datasets created through manual annotation, the NLP model combined fuzzy matching and embedding-based algorithms, achieving 95% accuracy, 98% specificity, and 92% sensitivity. The cohort was evenly split by gender, predominantly African American/Black (57%), with most patients aged 20–40 years (54%), and the majority relying on Medicaid (36%) or Medicare (28%). Notably, 70% of patients received antibiotics, and 11% were prescribed opioids. This study demonstrated the high prevalence of antibiotics and opioid prescriptions for dental pain in ED settings.
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Patel et al. (2025) studied this question.
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