Increasing access to specialist care with group medical visits: summary of a pilot in a post-crisis psychiatric clinic
Bibliographic record
Abstract
Background Group medical visits (GMVs) have strong evidence of acceptability and effectiveness in the management of chronic medical diseases. Adaptation of GMVs for psychiatric care has potential to increase access, decrease stigma and save costs. Despite promise, this model has not been widely adopted. Methods A novel GMV pilot was implemented for psychiatric care post-crisis among patients with primary mood or anxiety disorders who required medication management. Participants filled out PHQ-9 and GAD-7 scales at each visit in order to track their progress. After discharge, charts were reviewed for demographics, medication changes and symptom changes. Patient characteristics were compared between those who attended and those who didn't. Changes in total PHQ-9 and GAD-7 scores among attendees were assessed with paired t -tests. Results Forty-eight patients were enrolled between October 2017 and the end of December 2018, 41 of whom consented to participate. Of those, 10 did not attend, 8 attended but did not complete, and 23 completed. Baseline PHQ-9 and GAD-7 scores did not differ significantly between groups. Significant and meaningful reductions in PHQ-9 and GAD-7 scores from baseline to last visit attended occurred among those who attended at least 1 visit (decrease of 5.13 and 5.26 points, respectively). Conclusions This GMV pilot demonstrated feasibility of the model as well as positive outcomes for patients recruited in a post-crisis setting. This model has the potential to increase access to psychiatric care in the face of limited resources, however the failure of the pilot to sustain highlights challenges to be addressed in future pivots.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".