Impacts of the COVID-19 Pandemic on Primary Care Utilization: An Analysis of Primary Care Claims Data in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic disrupted primary health care systems worldwide, prompting rapid changes in how care was delivered. In Alberta, this included a significant shift from in-person to virtual care. This study examines trends in primary care utilization among Albertans during COVID-19 and the shift toward virtual care. METHODS: Repeated cross-sectional analyses were conducted from 2018/19 to 2022/23 using Alberta Health Practitioner Claims data. Utilization was measured as the proportion of Albertans with at least one visit and the annual visit rate per person. Annual percent change (APC) was calculated relative to the pre-pandemic year (2019/20) and stratified by demographics. FINDINGS: The proportion of Albertans with a primary care visit decreased by -9.55% in 2020/21 but recovered to -4.62% by 2022/23. Annual visit rates remained stable post-pandemic. The largest declines in 2020/21 were among children aged 5 to 11 (-38.42%), ≤4 (-33.42%), newborns (-30.36% to -25.49%), and those without health conditions (-20.9%). Virtual care accounted for 23.77% of visits in 2020/21, dropping to 14.43% by 2022/23. CONCLUSIONS: While fewer Albertans accessed primary care, visit rates remained stable due to virtual care. Further research is needed to assess the long-term impacts of COVID-19 on primary healthcare delivery.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".