Integrating public health and primary care: a framework for seamless collaboration
Bibliographic record
Abstract
Integration between public health and primary care is rising on the health policy agenda but the terms and concepts involved can be confusing. This article reviews the relevant literature and presents a new framework to help policymakers think through what they are aiming to achieve and why. We unpack different degrees and types of integration and show how they fit together. We argue that the merger of public health and primary care into a single entity with one aim, budget, and one multidisciplinary team isn’t necessarily the desired end-point for most health systems, but that seamless collaboration will likely improve patient and health system outcomes, save resources, and improve population outcomes. We recommend that efforts to foster better collaboration should take an activity-based approach, promoting alignment of teams, training, budgets, values and culture around specific tasks, and in proportion to need.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.096 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.018 | 0.069 |
| Scholarly communication | 0.035 | 0.031 |
| Open science | 0.008 | 0.037 |
| Research integrity | 0.017 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 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".