Changes in Service Delivery and Access to Rheumatologists Before and During the COVID-19 Pandemic in a Canadian Universal Healthcare Setting
Bibliographic record
Abstract
OBJECTIVE: To describe changes in service delivery and access to rheumatologists before and during the coronavirus disease 2019 (COVID-19) pandemic periods. METHODS: We conducted a population-based study in Ontario, Canada. Patient visits with rheumatologists were ascertained using billing claims data. Contact with rheumatologists was defined separately by the type of patient encounter (including office visits, telemedicine visits, and new patient consultations). Changes in the total weekly volume of encounters and monthly rates after COVID-19 public health measures were imposed were compared to expected baseline rates determined before pandemic onset (March 17, 2020). RESULTS: In the year prior to the pandemic, there were 289,202 patients (of which 96,955 were new consults) seen by 239 rheumatologists. In the 1 year following the pandemic onset, there were 276,686 patients (of which 86,553 were new consults) seen by 247 rheumatologists. In March 2020, there was an immediate 75.9% decrease in outpatient office visits and a rapid rise in telemedicine visits. By September 2021, 49.7% of patient encounters remained telemedicine visits. For new patient consultations, there was an immediate 50% decrease in visits at the pandemic onset, with 54.8% diverted to telemedicine visits in the first year of the pandemic versus 37.4% by September 2021. New rheumatology consultation rates continued decreasing over the study period. CONCLUSION: Rheumatology care delivery has shifted due to the pandemic, with telemedicine increasing sharply early in the pandemic and persisting over time. The pandemic also negatively affected access to rheumatologists, resulting in fewer new consultations and raising concerns for potential delays to diagnosis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".