Implementing population health management: an international comparative study
Bibliographic record
Abstract
PURPOSE: The purpose of this paper is to gain insight into how population health management (PHM) strategies can successfully integrate and reorganize public health, health care, social care and community services to improve population health and quality of care while reducing costs growth, this study compared four large-scale transformation programs: Greater Manchester Devolution, Vancouver Healthy City Strategy, Gen-H Cincinnati and Gesundes Kinzigtal. DESIGN/METHODOLOGY/APPROACH: Following the realist methodology, this explorative comparative case-study investigated PHM initiatives' key features and participants' experiences of developing such initiatives. A semi-structured interview guideline based on a theoretical framework for PHM guided the interviews with stakeholders (20) from different sectors. FINDINGS: Five initial program theories important to the development of PHM were formulated: (1) create trust in a shared vision and understanding of the PHM rationale to establish stakeholders' commitment to the partnership; (2) create shared ownership for achieving the initiative's goals; (3) create shared financial interest that reduces perceived financial risks to provide financial sustainability; (4) create a learning environment to secure initiative's credibility and (5) create citizens' and professionals' awareness of the required attitudes and behaviours. ORIGINALITY/VALUE: The study highlights initial program theories for the implementation of PHM including different strategies and structures underpinning the initiatives. These insights provide a deeper understanding of how large-scale transformation could be developed.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".