Provision of dental care by public health dental clinics during the COVID-19 pandemic in Alberta, Canada
Bibliographic record
Abstract
OBJECTIVES: This study aims to describe dental services provided to a low income population in dental public health settings during the first wave of COVID-19 pandemic in Alberta, Canada. METHODS: Routinely collected clinical data were recorded by dentists in electronic medical record files at Alberta's two Public Health Dental Clinics (PHDCs). Patient contact was via teledentistry or in person, respecting phased provincial pandemic restrictions. A descriptive analysis of data relating to all patients contacting PHDC with dental problems between 17 March - 31 October 2020 was undertaken and compared to equivalent pre-COVID 2019 data. RESULTS: In the period examined, 851 teledentistry consultations and 1031 in person visits were performed. Compared to the same period in 2019, 46% fewer patients were treated, representing a decrease in dental procedures: tooth extractions (17%), silver diamine fluoride applications (17%), endodontic treatments (82%) and fillings (84%). By contrast, prescriptions increased by 66% overall; representing 76%, 121% and 44% in antibiotics, non-opioid analgesics, and opioid analgesics respectively. In both years, antibiotics were the most prescribed drugs (66% in 2019 versus 62% in 2020) followed by non-opioid analgesics (28% in 2019 versus 33% in 2020); opioids accounted for the remainder (6.5% in 2019 and 5% in 2020). The largest drug prescription increases occurred during April-May 2020, when access to care was most restricted: antibiotics and non-opioid analgesics were 300% and 738% higher than the same time in 2019. CONCLUSIONS: Teledentistry and pharmacotherapy were used to triage and organise dental patients accessing care during the early stages of the pandemic. However, teledentistry did not replace definitive in person dental treatment, particularly for low income populations with high incidence of toothache and odontogenic infection. Reduced provision of dental procedures was accompanied by an increase in drug prescribing. Expedient access to care must be provided to address the dental needs of this population avoiding risks of further complications associated with infection and overprescribing antibiotics and opiates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".