Disruptions in Rheumatology Care and the Rise of Telehealth in Response to the COVID‐19 Pandemic in a Community Practice–Based Network
Bibliographic record
Abstract
OBJECTIVE: The effect of the COVID-19 pandemic on community-based rheumatology care and the use of telehealth is unclear. We undertook this study to investigate the impact of the pandemic on rheumatology care delivery in a large community practice-based network. METHODS: Using a community practice-based rheumatologist network, we examined trends in in-person versus telehealth visits versus canceled visits in 3 time periods: pre-COVID-19, COVID-19 transition (6 weeks beginning March 23, 2020), and post-COVID-19 transition (May-August). In the transition period, we compared patients who received in-person care versus telehealth visits versus those who cancelled all visits. We used multivariable logistic regression to identify factors associated with canceled or telehealth visits. RESULTS: Pre-COVID-19, there were 7,075 visits/week among 60,002 unique rheumatology patients cared for by ~300 providers practicing in 92 offices. This number decreased substantially (24.6% reduction) during the COVID-19 transition period for in-person visits but rebounded to pre-COVID-19 levels during the post-COVID-19 transition. There were almost no telehealth visits pre-COVID-19, but telehealth increased substantially during the COVID-19 transition (41.4% of all follow-up visits) and slightly decreased during the post-COVID-19 transition (27.7% of visits). Older age, female sex, Black or Hispanic race/ethnicity, lower socioeconomic status, and rural residence were associated with a greater likelihood of canceling visits. Most factors were also associated with a lower likelihood of having telehealth versus in-office visits. Patients living further from the rheumatologists' office were more likely to use telehealth. CONCLUSION: COVID-19 led to large disruptions in rheumatology care; these disruptions were only partially offset by increases in telehealth use and disproportionately affected racial/ethnic minorities and patients with lower socioeconomic status. During the COVID-19 era, telehealth continues to be an important part of rheumatology practice, but disparities in access to care exist for some vulnerable groups.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".