General practitioners: Between integration and co-location. The case of primary care centers in Tuscany, Italy
Bibliographic record
Abstract
Healthcare systems have followed several strategies aimed at integrating primary care services and professionals. Medical homes in the USA and Canada, and primary care centres across Europe have collocated general practitioners and other health and social professionals in the same building in order to boost coordination among services and the continuity of care for patients. However, in the literature, the impact of co-location on primary care has led to controversial results. This article analyses the possible benefits of the co-location of services in primary care focusing on the Italian model of primary care centres (Case della Salute) in terms of general practitioners' perception. We used the results of a web survey of general practitioners in Tuscany to compare the experiences and satisfaction of those general practitioners involved and not involved in a primary care centre, performed a MONAVA and ANOVA analysis. Our case study highlights the positive impact of co-location on the integration of professionals, especially with nurses and social workers, and on organizational integration, in terms of frequency of meeting to discuss about quality of care. Conversely, no significant differences were found in terms of either clinical or system integration. Furthermore, the collaboration with specialists is still weak. Considering the general practitioners' perspective in terms of experience and satisfaction towards primary care, co-location strategies is a necessary step in order to facilitate the collaboration among professionals and to prevent unintended consequences in terms of an even possible isolation of primary care as an involuntary 'disintegration of the integration'.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".