What role can education play in integrated care? Lessons from the ECHO (Extensions for Community Health Outcomes) Concussion program
Bibliographic record
Abstract
Purpose Design, implementation, and evaluation are all important for integrated care. However, they miss one critical factor: education. The authors define “integrated care education” as meaningful learning that purposefully supports collaboration and the development of adaptive expertise in integrated care. The ECHO (Extensions for Community Health Outcomes) model is a novel digital health solution that uses technology-enabled learning (TEL) to facilitate, support, and model integrated care education. Using ECHO Concussion as a case study, the authors describe the effects of technology-enabled integrated care education on the micro-, meso-, and macro-dimensions of integrated care. Design/methodology/approach This case study was constructed using data extracted from ECHO Concussion from video-archived sessions, participant observation, and internal program evaluation memos. The research team met regularly to discuss the development of relevant themes to the dimensions of integrated care. Findings On the micro-level, clinical integration occurs through case-based learning and the development of adaptive expertise. On the meso-level, professional integration is achieved through the development of the “specialist generalist,” professional networks and empathy. Finally, on the macro-level, ECHO Concussion and the ECHO model achieve vertical and horizontal system integration in the delivery of integrated care. Vertical integration is achieved through ECHO by educating and connecting providers across sectors from primary to quaternary levels of care. Horizontal integration is achieved through the establishment of lateral peer-based networks across sectors as a result of participation in ECHO sessions with a focus on population-level health. Originality/value This case study examines the role of education in the delivery of integrated care through one program, ECHO Concussion. Using the three dimensions of integrated care on the micro-, meso-, and macro-levels, this case study is the first explicit operationalization of ECHO as a means of delivering integrated care education and supporting integrated care delivery.
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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 | 0.035 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 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".