Supporting Better Access to Chronic Pain Specialists: The Champlain BASE <sup>™</sup> eConsult Service
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: (Building Access to Specialists through eConsultation) eConsult service can improve access to specialist care for patients with chronic pain by facilitating electronic communication between primary care providers (PCPs) and specialists. We explored the content of eConsult cases sent to chronic pain specialists to identify the major themes emerging from exchanges between PCPs and specialists regarding patients with chronic pain. METHODS: We conducted a thematic analysis of eConsult cases submitted to chronic pain specialists between April 1, 2011 and October 31, 2014, using a constant comparison approach. RESULTS: PCPs submitted 128 cases to chronic pain specialists during the study period. The study team coded 48 cases before data saturation was reached. PCPs sought advice for treating patients with chronic pain arising from a range of medical problems, and who frequently struggled with issues of mental health, substance dependence, and social complexity. Specialists responded with advice on pain management and treatment, directed PCPs to published guidelines and community resources, and validated the PCPs' frustration or concerns. Specialists provided instruction on safe opioid prescribing and how to identify and manage potential cases of substance dependence. CONCLUSION: Providing care to patients with chronic pain is a challenge for PCPs, who often experience frustration at their inability to provide a definitive solution for patients. Specialists offered invaluable feedback not only through guidance and advice, but also with sympathy and encouragement.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it