Innovating the treatment of COPD exacerbations: a phone interactive telesystem to increase COPD Action Plan adherence
Bibliographic record
Abstract
Introduction: Self-management interventions with Written Action Plans and case management support have been shown to improve outcomes in patients with chronic obstructive pulmonary disease (COPD). Novel telehealth technologies may improve self-management interventions. The objectives of this study were to determine whether the use of an interactive phone telesystem increases Action Plan adherence, improves exacerbation recovery and reduces healthcare use in a real-life practice of a COPD clinic. Methods: Initially, 40 patients were followed by a COPD telesystem for 1 year. Detailed data from patients' behaviours during exacerbations was recorded. The telesystem use was then extended to 256 patients from a real-life COPD clinic. Healthcare utilisation for the year before and after telesystem enrolment was then assessed through hospital administrative databases. Results: Thirty-three of the 40 patients completed the initial 1-year study. Eighty-one exacerbations were reported in the 1-year follow-up. Action Plan adherence was observed for 72% of the exacerbations and those who were adherent had a significantly faster exacerbation recovery time. The large-scale implementation of the telesystem resulted in a significant decrease in the proportion of patients with ≥1 respiratory-related emergency room (ER) visits (120 before vs 110 after enrolment, p<0.001) and with ≥1 COPD-related hospitalisations (75 before vs 65 after enrolment, p<0.001). Discussion: COPD Written Action Plan adherence was further enhanced with the use of telehealth technologies in a specialised clinic with experience in COPD self-management. Patients followed by the telesystem recovered faster from exacerbations and had a further decrease in COPD-related ER visits and hospitalisations. Trial registration number: NCT02275078.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".