A Medicoeconomic Evaluation of a Telehealth Platform for Elective Outpatient Surgeries: Protocol for a Randomized Controlled Trial (Preprint)
Bibliographic record
Abstract
BACKGROUND The number of elective outpatient surgeries in Canada has increased markedly in the last 10 years. However, unanticipated cancellations on the day of surgery and adverse postoperative events are frequent. Modern technologies have been shown to be of great help in the medical field in improving patient care. Thus, it is likely that dedicated technologies could also significantly improve surgical outpatients’ pathways. Therefore, the department of anesthesiology at the University of Montreal Medical Center, in collaboration with LeoMed, a telemedicine platform, has developed a telehealth solution to offer more efficient perioperative support and follow-up for patients undergoing ambulatory surgery. OBJECTIVE The objective is to evaluate the medicoeconomic benefit of a dedicated perioperative telehealth platform for patients undergoing day surgery. Our hypothesis is that this dedicated telecare solution will allow more efficient patient care, which will reduce all types of medical costs related to day surgery pathways. METHODS This study is a single-center, single-blinded, 2-group randomized controlled trial. One thousand patients aged over 18 years with internet access who are scheduled to undergo ambulatory surgery will be enrolled and randomized either to follow a perioperative path that includes a patient-tailored perioperative digital app via the LeoMed telecare platform for 1 month or to follow the standard of care, which does not offer personalized digital support. The primary outcome will be to evaluate the cost-effectiveness of the telecare platform, assessing direct costs from factors such as unanticipated cancellations on the day of surgery due to preoperative instructions not being followed, calls to the local health information line, calls to the provincial health information line, emergency department consultations, unplanned readmissions, or medical visits for problems related to the surgical procedure within the first 30 days after the intervention. The secondary outcome will be to evaluate cost utility using a questionnaire assessing quality-adjusted life years. A blinded independent research team will analyze outcomes. All data will be analyzed according to the intention-to-treat principle. A sample size of 500 subjects in each group was calculated to detect a 21% reduction in postoperative complications with a power of 90%. This study has been approved by the ethics board of Centre hospitalier de l’Université de Montréal (University of Montreal Health Centre). No employee of LeoMed was involved in the study conception, and none will be involved in either data collection or analysis. RESULTS Results of this trial will be useful to determine the economic benefit of a telecare platform specifically developed for surgical outpatient pathways. CONCLUSIONS We believe that the deployment of a dedicated perioperative telehealth app will lead to better patient care and fewer postoperative complications, which will lower all types of costs related to surgical outpatient care. CLINICALTRIAL ClinicalTrials.gov NCT04948632; https://ClinicalTrials.gov/ct2/show/NCT04948632 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/44006
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
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 | 0.026 | 0.028 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.069 | 0.010 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".