Integrated Community Collaborative Care for Seniors with Depression/Anxiety and any Physical Illness
Bibliographic record
Abstract
BACKGROUND: We report on the feasibility and effectiveness of an integrated community collaborative care model in improving the health of seniors with depression/anxiety symptoms and chronic physical illness. METHODS: This community collaborative care model integrates geriatric medicine and geriatric psychiatry with care managers (CM) providing holistic initial and follow-up assessments, who use standardized rating scales to monitor treatment and provide psychotherapy (ENGAGE). The CM presents cases in a structured case review to a geriatrician and geriatric psychiatrist. Recommendations are communicated by the CM to the patient's primary care provider. RESULTS: 187 patients were evaluated. The average age was 80 years old. Two-thirds were experiencing moderate-to-severe depression upon entry and this proportion decreased significantly to one-third at completion. Qualitative interviews with patients, family caregivers, team members, and referring physicians indicated that the program was well-received. Patients had on average six visits with the CM without the need to have a face-to-face meeting with a specialist. CONCLUSION: The evaluation shows that the program is feasible and effective as it was well received by patients and patient outcomes improved. Implementation in fee-for-service publicly funded health-care environments may be limited by the need for dedicated funding.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".