Improving value and access to specialty medical care for families: a pediatric surgery telehealth program
Bibliographic record
Abstract
Background: In Canada, access to subspecialty surgical services for children imposes inconvenience and financial hardship on geographically remote families. The purpose of this study was to evaluate a recently implemented pediatric surgical telehealth pilot program from the family and provider perspectives. Methods: Enabled by an existing telehealth infrastructure for pediatric subspecialty medicine and mental health, a pilot telehealth program for surgical consultation was established by a single surgeon in British Columbia. Following establishment of eligibility criteria, patients from remote communities requiring new consultation or clinical follow-up were offered a telehealth alternative. At the end of the encounter, both the parent and patient (if appropriate) provided feedback via a questionnaire. Provider satisfaction was also assessed via a questionnaire. We estimated costs avoided and analyzed data on pediatric surgery consultation wait time. Results: Between September 2014 and November 2017, 80 patients were seen in 19 remote telehealth centres, 23 as new referrals and 57 in follow-up consultation. Among new referrals, the commonest diagnosis was chest wall deformity. The average travel distance avoided was 705 km, with an estimated direct cost avoidance of $585. Sixty-four families (80%) completed the questionnaire. Almost all (63 [98%]) indicated high overall satisfaction with the telehealth experience. Provider satisfaction was similarly high, in terms of both the technology user interface and clinical effectiveness. Overall pediatric surgical consultation wait times were unaffected. Conclusion: Implementation of telehealth technology in a pediatric surgical practice offered high value to patients/families and, from the provider’s perspective, yielded an acceptable alternative to in-person assessment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".