Use of Telemedicine in Chronic Pain Consultation
Bibliographic record
Abstract
OBJECTIVES: Telemedicine has been used extensively in various settings, including monitoring patient treatment response and counseling. However, there are few data on the application of telemedicine to chronic pain patients. The present study was the first pilot project to determine whether telemedicine technology for chronic pain consultation was feasible, cost-saving, and satisfactory to patients and pain physicians. METHODS: A prospective pilot study was conducted on chronic pain patients requiring follow-up consultations using telemedicine technology. Patients were interviewed by phone following the consultation. RESULTS: Eleven telemedicine anesthesia consultations involving eight patients (age 42+/-9 years; six men, two women) were performed. All were follow-up consultations. The average distance from patients' home to the clinic was 314+/-170 km. The reasons for consultation were for update of patient progress (10/11), medication change (6/11), and counseling (3/11). The time to complete the consultation was 24.5+/-9.5 minutes. The data for the time and the cost that the patient spent on the consultation are presented as median and 25% to 75% interquartile range. Patients having telemedicine consultations spent 0.9 hours (0.83-1) and Canadian dollar 3 (dollar 2-4) versus an estimate of 8 hours (6-8) and Canadian dollar 80 (dollar 46-260) for a conventional consultation (both P<0.005). Telemedicine consultation was found to be highly satisfactory to the patient and the consulting and attending anesthesiologists. CONCLUSIONS: This pilot study indicates that telemedicine follow-up consultations for chronic pain patients are feasible and cost-saving. Patients and anesthesiologists were highly satisfied with telemedicine consultation. Patients reported a significant saving in time and cost compared with a conventional consultation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".