P.069 Development of a streamlined multi-disciplinary care pathway for compression neuropathies
Bibliographic record
Abstract
Background: Care for patients with compression neuropathies (carpal tunnel syndrome, ulnar neuropathy) is often fragmented, uncoordinated, and slow. Patients go through multiple steps (neurology consultation, nerve testing, ultrasound, splints, injection, surgical opinion, surgery) with waits between each step. We used a Value-Based Health Care (VBHC) model to develop a multidisciplinary clinic with a novel care pathway. Methods: A Shared Care initiative supported the development of an Integrated Practice Unit (IPU). Key multidisciplinary team members were identified. Participants attended a curated three part VBHC workshop. Process mapping enabled identification of efficiencies. Results: 14 team members participated in the workshops. Condition specific outcome measures were identified (Boston CTS measure, 10-point touch, MRC strength and pain scale) and will be collected longitudinally. Criteria and clinical pathways were developed for mild, moderate, and severe carpal tunnel syndrome. Resource materials for patients and providers were developed. Conclusions: A VBHC framework supported development of a novel clinic for compression neuropathy. Responsibility for the full cycle of care rests with the IPU. Systematically tracking functional outcome measures enables quality improvement. By streamlining the patient journey and substantially reducing wait times between steps, the new care pathway reduces complexity and improve outcomes. Evaluation of impact if this new clinical model is ongoing.
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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".