Cost Benefit and Carbon Emission Saving Analysis of Remote Cochlear Implant Programming
Bibliographic record
Abstract
OBJECTIVE: To assess the financial benefits and carbon emission savings associated with performing virtual-synchronous remote programming and troubleshooting following cochlear implant (CI) placement for patients who live in remote regions. METHODS: CI users living ≥ 100 km from the implant center with ≥ 1 month CI experience were included. Participants were either assigned to home visits using a portable laptop (Remote Laptop; n = 20) or attended visits through the nearest Remote Hosted Site (n = 34). Direct costs in Canadian dollars from a Ministry of Health perspective and carbon emissions were compared between remote and in-person appointments at the implant center. RESULTS: Median distances between participants' homes to the implant center were 574 km (Remote Laptop) and 999 km (Remote Hosted Site). Average costs for both groups of remote care were lower compared with in-person appointments at the implant center (Remote Laptop: $180.70 vs. $431.61, p = 0.002; Remote Hosted Site: $155.34 vs. $1110.89, p < 0.001). Total cost reductions were $5018.23 and $32,488.76 with cost-to-benefit ratios of 2.39 and 7.15 for Remote Laptop and Remote Hosted Site groups, respectively. Net carbon emission benefits were 2200.00 kg and 5691.50 kg with net carbon benefit ratios of 512.63 and 5.25 for Remote Laptop and Remote Hosted Site, respectively. CONCLUSION: Virtual synchronous remote CI programming and troubleshooting generates cost savings in post-surgical care. Additionally, it achieves remarkable carbon emissions savings. More widespread adoption is expected, especially for those who reside far from implant centers.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".