Use of Telemedicine for Initial Consultations in Elective Orthopaedics—Results from a Large Volume Centre
Bibliographic record
Abstract
Category: Healthcare Delivery Introduction/Purpose: Telehealth and telemedicine are at the heart of healthcare Vision for several countries including Canada, U.S.A, Scotland, etc; and and the aim is to use technologies to transform the way health and is delivered. Deployed thoughtfully and carefully, telehealth and telecare can help generate efficiencies through more flexible use of our workforce capacity and by reducing travel and minimising access delays. In line with this we wanted to use telemedicine for doing preoperative consultations for elective foot/ankle and lower limb arthroplasty procedures in patients referred from remote parts of the country to our hospital. The purpose of our study was to prove that telemedicine clinics (or Tele clinics) are just as safe, effective and satisfactory as face to face interactions between doctors and their patients. Methods: Two studies were conducted at this hospital between 2015-16. The first was a prospective pilot study of 50 new patients who were all seen using two different consultation rooms; with the patient along with a physiotherapist in one room, and the surgeon in another. Patients were seen via the Telemedicine unit without being aware that the surgeon was in the same building, and were then asked to rate their experience. The unanimous positive feedback received from this pilot study encouraged us to start using Tele clinics for initial consultations on a regular basis. The second study is a retrospective analysis of the safety and quality of the Tele clinics during a twelve months period. Results: 4 surgeons saw 320 patients in the Tele clinics over the study period of 12 months for foot/ankle as well as lower limb arthroplasty conditions. The number of patients who required surgery and the number of additional investigations carried out were similar to the ones from regular clinics. Feedback from patients remained very high for the Tele-clinics. Conclusion: Tele-clinics are largely used for reviewing patients after surgery. Our study shows that Tele-clinics can also be used for initial consultation for routine orthopaedic conditions, and are as safe and effective as face to face consultations. This provides an opportunity to treat patients in new ways and help manage rising costs and demand.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".