Clinical telemedicine utilization in paediatric nephrology at a tertiary care centre
Bibliographic record
Abstract
Purpose: Telemedicine is an emerging tool that offers medical consultations to patients with limited access to subspecialty care. To date, the use of telemedicine in Canadian medical practices has not been studied in depth. This study aims to characterize the three different telemedicine clinic models in use at the paediatric nephrology program at the Children’s Hospital of Western Ontario and the patient population they served. Methods: To complete this retrospective study, all paediatric nephrology telemedicine consultations provided by one physician from September 30, 2010 to July 13, 2016 were analyzed, which comprised 264 separate consultations with 87 patients. Results: The number of consults increased from 0.25 per month to 8.78 per month between 2010 and 2016, with the most substantial increase seen from 2014 onwards with the establishment of the Windsor block clinics. The patient population had a bimodal age distribution across a geographical distance of 220.3 km to 1371.31 km. Urinary tract infections were the most frequent reason for the consultation. Conclusion: Of the three models described in this study, the block clinic model had the most substantial impact on increasing telemedicine services for paediatric nephrology patients. CORRECTION, September 7, 2017: In the Methods section of this article, the author AR is incorrectly referred to as a nurse practitioner. AR is in fact a registered nurse (RN). We regret that this error was included.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.006 | 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".