Family doctors providing primary care to patients with mental illness in a tertiary care facility.
Bibliographic record
Abstract
PROBLEM ADDRESSED: Individuals with severe mental illness have an increased burden of physical comorbidities. Physical concerns of patients admitted to hospital for mental health reasons might be addressed by multiple specialists, leading to fragmented care and high costs to the system, when many of these concerns could be addressed by primary care. OBJECTIVE OF PROGRAM: The Family Doctor Outreach Clinic (FDOC) aims to provide rapid consultations for common concerns, to provide consultations for complex chronic disease and addictions, and to identify gaps in community care that contribute to patients' potential readmission to hospital. The FDOC is a simple and novel collaborative program of care in a tertiary care setting. PROGRAM DESCRIPTION: Members of the Department of Family Medicine at St Paul's Hospital in Vancouver, BC, have been providing consultation services for patients admitted to the 4 mental health wards (total of 108 beds). Using a prospective cohort of consecutive consultations (N = 104) from July to August 2014, the study team collected data on details of current admissions, connections to community primary care, and reasons for consultations. CONCLUSION: Including family physicians in the care of mental health inpatients, as is done at the FDOC, might avert referrals to specialist services and provide a bridge between acute care and community family practice.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.002 |
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".