Achieving More Equitable Complex Concussion Management: Lessons from ECHO Concussion, a Telemedicine Education Program
Bibliographic record
Abstract
CONTEXT: Concussions, a form of mild traumatic brain injury, are diagnosed in 150,000 Ontarians annually, resulting in disruptions to work, school, and sport. Concussion management is complex: addressing and correcting misinformation, variable onset of symptoms, urban/rural health service disparities, and the number of healthcare and non-healthcare professionals involved in case management. The ECHO (Extensions for Community Healthcare Outcomes) model provides an ideal platform for dissemination of existing best practice guidelines and standards of care in common, chronic, and complex conditions. ECHO Concussion aims to teach Primary Care Providers (PCPs) a comprehensive approach to concussion diagnosis and management across the continuum. OBJECTIVE: To illustrate complex concussion management and how ECHO Concussion supports PCPs and patient management in Ontario, Canada. METHODS: An in-depth case study of ECHO Concussion was performed through analysis of videoarchived weekly sessions and program implementation and evaluation documents. All documents were reviewed for content relating to complex concussion management and ECHO-generated support and recommendations. Thematic content analysis was conducted on all recorded sessions and program documents to deeper understanding and framework for concussion management. The study team discussed and reconciled discrepancies in themes until consensus was reached. RESULTS: Successful program outcomes from the ECHO Concussion program include increased PCP self-efficacy, increased knowledge, and high participation satisfaction rates. Since ECHO sessions are interprofessional and PCPs participate from a variety of practice settings, they also gain insight and empathy regarding the roles and responsibility for concussion management among other professions, thus impacting the management of concussion in the community. Through the navigation and negotiation of information which is not always evidence-based, clinicians also observe how to tactfully address misinformation in the clinical setting. CONCLUSION: Concussion management is complex for a number of reasons and a telemedicine education program like ECHO Concussion may be beneficial for frontline PCPs. Not only does ECHO Concussion foster interprofessional collaboration and address important concussion misinformation, ECHO sessions also foster a community of practice, a critical part in developing PCPs’ confidence in clinical management of complex conditions.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".