Telehealth pulmonary rehabilitation: A review of the literature and an example of a nationwide initiative to improve the accessibility of pulmonary rehabilitation
Bibliographic record
Abstract
Several different applications of telehealth technologies have been used in the care of respiratory patients, including telemonitoring, teleconsultations, tele-education, and telehealth-pulmonary rehabilitation (PR). Telehealth technology provides an opportunity to assist in the management of chronic respiratory diseases and improve access to PR programs. While there is inconclusive evidence as to the effectiveness of telemonitoring to reduce healthcare utilization and detection of exacerbations, teleconsultations have been shown to be an effective means to assess patients' disease prior to the initiation of PR, and telehealth PR has been shown to be as effective as institution-based PR at improving functional exercise capacity and health-related quality of life. To improve PR access across Canada and ensure a high standard of program quality, a team of clinicians and researchers has developed and begun to implement a national standardized PR program that can be delivered across different settings of practice, including remote satellite sites via telehealth PR. The program has adapted the "Living Well with COPD" self-management program and includes standardized reference guides and resources for patients and practitioners. A progressive and iterative process will evaluate the success of program implementation and outcomes. This initiative will address nationwide accessibility challenges and provide PR content as well as evaluations that are in accordance with clinical standards and established self-management practices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".