A Cost-Minimization Analysis of Orthopaedic Consultations Using Videoconferencing in Comparison with Conventional Consulting
Bibliographic record
Abstract
We compared the costs of conventional outpatient visits to the surgical department of the University Hospital of Oulu with those of videoconferencing between the primary care centre in Pyhäjärvi and the University Hospital (separated by 160 km). The cost data were obtained from a randomized controlled trial that included 145 first-admission and follow-up orthopaedic patients. In the telemedicine group the annual fixed costs were 6074 in the hospital and 3910 in the primary care centre. The additional variable costs were 2 in the hospital and 19 in primary care. At a workload of 100 patients, the total cost, including travel and indirect costs, was 87.8 per patient in the telemedicine group and 114.0 per patient in the conventional group (i.e. a total cost saving from the use of teleconsultation of 2620). A cost-minimization analysis showed that telemedicine was less costly for society than conventional care at a workload of more than 80 patients per year. If the distance to specialist care were reduced from 160 km to 80 km, the break-even point increased to about 200 patients per year. Wider utilization of the videoconferencing equipment for other purposes, or the use of less expensive videoconferencing equipment, would make services cost saving even at relatively short distances. The study showed that orthopaedic outpatient telecare can be cost minimizing.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".