Experience With Store-and-Forward Consultations in Providing Access to Pediatric Endocrine Consultations in Low- and Middle-Income Countries
Bibliographic record
Abstract
Pediatric specialists are often unavailable in low- and middle-income countries. As part of multiple professional associations' efforts to improve access to endocrine expertise globally, a pediatric endocrine teleconsultation network was established on a store-and-forward teleconsultation platform to facilitate focused, language-appropriate advice that can be kept for future reference while bypassing real-time video-conferencing, and obviating the need for a scheduled appointment. User information was recorded, and quality statistics on network performance and qualitative evaluation by referring physicians were analyzed. Over a 3-year period, 81 referrers (88% from Haiti) and 13 pediatric endocrinologists registered onto the network and discussed 47 pediatric endocrine cases, exchanging a total of 412 messages for a median of 7 messages (IQR 5, 11) per case. Diagnoses spanned the spectrum of pediatric endocrine disorders. According to referrers, an appropriate expert was consulted and an answer provided sufficiently quickly in 100% of cases. The answer was well-adapted to their environment in 86%, and referrers were able to follow the advice given in 72%. All but one referrer found the advice helpful, it clarified the diagnosis in 88%, assisted with management in 93%, improved patient's symptoms in 77%, improved function in 77%, and was considered cost-saving in 50%. Perceived benefits of the consultations were academic instruction, setting-adapted advice beyond the scope of guidelines or textbooks, and advancement in the diagnostic process. Pediatric endocrine remote store-and-forward consultations in low- and middle-income countries may provide a reasonable alternative to face-to-face visits, providing clinical and educational benefit, and a potential for cost-saving.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".