Integration through education: utilizing project ECHO to mitigate fragmentation and support adaptive expert care in HIV Psychiatry
Why this work is in the frame
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Bibliographic record
Abstract
Purpose Care of complex patients requires collaboration across hospital and community settings. Yet there is little recognition of the capabilities that healthcare workers need to effectively implement integrated care. An adaptive expertise theoretical framework can inform educational efforts that aim to give providers the abilities to navigate complexity and ambiguity in the healthcare system, including across hospital and community settings. Prior education research in the HIV sector has demonstrated that adaptive expert skills can be cultivated through education that emphasizes perspective exchange, inviting uncertainty in practice and integration of diverse perspectives on care. Design/methodology/approach These principles informed the creation of an Extension for Community Healthcare Outcomes (ECHO) in HIV Psychiatry – the first ECHO directed at a non-clinical, community health worker (CHW) audience. The goal was to improve informal collaborations across hospitals and communities. Findings Participation in the ECHO was robust, with significant on-camera engagement. Participants attributed success of the ECHO to key themes: explicit value placed on all kinds of knowledge (not simply clinical knowledge), emphasis on approaches for navigating ambiguity and complexity and engagement in perspective exchange for provision of integrated, team-based care. Future cycles of ECHO HIV Psychiatry are being pursued, with a focus on the development of adaptive expert capabilities and the impact on integration of care between community and hospital services. Originality/value To our knowledge, this is the only ECHO that is specifically aimed at frontline CHWs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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