2025 Studies in health technology …

Painful Prescriptions: Opioid and Antibiotic Use for Dental Pain in the Emergency Department.

, , ,

Studies in health technology and informatics Vol. 329 : 362-366 • Aug 2025

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.

No clinical trial protocols linked to this paper

Clinical trials are automatically linked when NCT numbers are found in the paper's title or abstract.
PICO Elements

No PICO elements extracted yet. Click "Extract PICO" to analyze this paper.

Paper Details
MeSH Terms
Associated Data

No associated datasets or code repositories found for this paper.

Related Papers

Related paper suggestions will be available in future updates.