Medico-economic Evaluation of a Telehealth Platform for Elective Outpatient Surgeries: A Randomized Controlled Trial (Preprint)
Bibliographic record
Abstract
BACKGROUND The increasing prevalence of ambulatory surgeries has highlighted the need for effective postoperative follow-up. While telemedicine represents a promising option for perioperative support and postoperative monitoring, evidence of its actual benefits remains limited. OBJECTIVE To evaluate the medico-economic impact of a personalized telemedicine platform for postoperative follow-up in day-surgery patients in terms of cost-effectiveness and cost-utility. METHODS Design and Setting: This single-blinded with two-group randomized controlled trial was conducted at the Centre hospitalier de l’Université de Montréal (CHUM) from August 2022 to September 2023. Participants: Adults undergoing elective day surgery were randomized into two groups: the intervention group, which received postoperative follow-up via the LeoMed® telemedicine platform, and the control group, which received standard care. The study adhered to ethical standards and was registered with ClinicalTrials.gov (NCT04948632). Intervention: The intervention group used a personalized telehealth platform offering preoperative education, psychological support, and postoperative monitoring through daily follow-up forms sent to patients’ smartphones. Alerts generated by patient responses were reviewed by CHUM’s telehealth support unit. Main Outcomes and Measures: The primary outcome was unanticipated healthcare utilization, including emergency visits, readmissions, and medical consultations within 30 days post-procedure. Secondary outcomes included gained quality-adjusted life years (QALY), patient satisfaction, healthcare costs, and greenhouse gas emissions. RESULTS Of 1,411 patients screened, 1,214 were randomized, with 436 in the intervention group and 445 in the control group analyzed. No significant differences in unanticipated healthcare utilization or costs were observed. The intervention group demonstrated a statistically significant QALY gain at postoperative day 14 (0.002, p = 0.013), but the difference was no longer significant at day 30 (0.001, p = 0.143). However, patient satisfaction was significantly higher in the intervention group at both days 14 (p = 0.018) and 30 (p < 0.001). CONCLUSIONS This trial demonstrates the potential of telemedicine platforms to enhance postoperative care in ambulatory surgery settings. While no significant reductions in healthcare utilization were observed, the intervention improved QALYs and patient satisfaction, suggesting potential cost-utility benefits. Larger trials are needed to confirm these findings and explore the impact on long-term recovery and healthcare savings. CLINICALTRIAL ClinicalTrials.gov Identifier: NCT04948632 INTERNATIONAL REGISTERED REPORT RR2-10.2196/44006
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 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".