Patient and provider perspectives on telemedicine use in Canadian gastroenterology clinics during the COVID-19 pandemic: a survey study
Bibliographic record
Abstract
Abstract Background Telemedicine has revolutionized access to medical care. This was particularly palpable during the COVID pandemic and within gastroenterology. Telehealth can improve access to patients remotely, and lead to high patient and clinician satisfaction. However, questions remain surrounding patient selection and provider considerations. We conducted a Canadian study to examine patient and provider preferences and experiences in telehealth. Methods An anonymous online survey was conducted amongst patients of an urban gastroenterology practice, as well as Canadian gastroenterologists, evaluating experiences and preferences in utility of telemedicine. Results Of 1236 patients contacted, 181 (15%) respondents were aged 18–89, 60% were female, and 58% had inflammatory bowel disease (IBD). Patient satisfaction with telehealth was high across all characteristics. Patients used both phone calls (61%) and video/audio applications (50%); higher use of phone calls was associated with older age (p = 0.02). Patients living more than 30km from clinic and with IBD were more likely to prefer telehealth visits (p < 0.01). Most providers (96%) and patients (96%) believed that telehealth use should continue for certain patients or follow up visits after the pandemic. Of 100 providers contacted, 25 respondents reported using phone calls (96%) and video/audio applications (44%). Providers perceived follow up of benign endoscopic pathology (96%) and general follow up visits (92%) to be most suitable for telehealth. Conclusion Canadian gastroenterology providers and patients appreciate telehealth and favor continued use after the pandemic. Consideration of patient factors such as age, distance, health issue, and follow up status can further optimize ongoing telehealth options.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| 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".