Integration between general practice and mental health services in Italy: guidelines for consultation-liaison services implementation
Bibliographic record
Abstract
PURPOSE: This paper illustrates some guidelines for the implementation of Consultation-liaison services in contexts where GPs work alone. We present some activity data of our experience in the period 1999-2004 and a critical evaluation of what works and what does not work. CONTEXT: In Italy single-sited spontaneous initiatives of co-operation and integration between general practice and psychiatry have been implemented in many regions. Recently, the Italian Health Care Government has begun to encourage integration between primary and secondary care for the management of mental health. The Bologna Consultation-liaison Service opened in 1999 in one area. The service was first located in the Community Mental Health Centre and subsequently in a medical non-psychiatric outpatient service. In 2002, the services were implemented in the overall city area, and the Bologna Consultation-liaison Service had its own office in the centre of the town. DATA SOURCE: Data have been collected by reviewing clinical charts. They include clinical (mental status examination, progress notes) and socio-demographic data, assessment scales that measure psychological distress and disability, reports for GPs, and consultation outcome. CONCLUSION: A consultation-liaison service like the one proposed in this paper could contribute to an efficient and fully-integrated collaborative management of common psychiatric disorders, reducing the use of mental health services.
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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 | 0.093 | 0.106 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".