Abstract

To assess the prevalence of dental emergency visits (DEV) involving pain relief and their relationship with socio-economic and clinical factors in an Australian representative sample in the primary care setting. Data on reason for visit and patient characteristics were collected from a representative random sample of Australian dentists in private practice surveyed in 2009-2010. Information regarding socio-economic (gender, age, health insurance) and clinical factors (number of teeth, number of decayed teeth, diagnosis and reason for visit [DEV, check-up, other reasons not involving pain relief]) were retrieved from compiled questionnaires. Descriptive statistics were reported, and Poisson regression models were used to assess the association between socio-economic and clinical factors and DEV. Prevalence ratio (PR) and 95% confidence interval (CI) were calculated. A total of 1148 dentists responded (67%), resulting in records from 6504 patients. The overall prevalence of DEV was 20.8%. The unadjusted analysis, according to the reason of visit, revealed the following predictors for DEV: male gender (PR=1.18; 95% CI=1.08-1.29), age 18-64years (PR=2.70; 95% CI=2.19-3.33) and over 65years (PR=2.64, 95% CI=2.10-3.32), uninsured patients (PR=1.36; 95% CI=1.24-1.49), patients with <20 teeth (PR=1.19; 95% CI=1.06-1.33), decayed teeth (PR=1.64; 95% CI=1.48-1.81). After adjustment for confounding factors (gender, age, insurance status, number of teeth and decayed teeth) apart from 'dental trauma' (PR=1.37), all remaining diagnoses had lower PR ('other' PR=0.19, 'decay' PR=0.34, 'periodontal' PR=0.51, 'failed restoration' PR=0.45) compared with 'pulp/periapical disease'. In the primary care setting, the diagnoses 'pulp/periapical' and 'dental trauma' had a stronger association with DEV compared with visits not involving relief of pain. Both socio-economic (male gender, older age and uninsured individuals) and clinical factors (tooth loss, decayed teeth, endodontic diseases and dental trauma) were identified as independent risk indicators for DEV in this population. Future public health policies should include specific preventive strategies addressing these factors, aiming to reduce the need for DEV.

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