Generalist-led hospital models and their alignment with value-based care: a systematic review protocol
Bibliographic record
Abstract
INTRODUCTION: Value-based care focuses on delivering high-quality care while managing costs. Generalist-led hospital models, with generalist physicians playing a central role, have emerged as an approach to achieve value-based care goals. However, the evidence on their effectiveness remains mixed. This systematic review will synthesise evidence on the impact of generalist-led models on patient outcomes, healthcare costs and resource utilisation compared with traditional models. METHODS AND ANALYSIS: We will search PubMed, Web of Science, Embase, CINAHL, Medline, Cochrane Library, PsycINFO and Scopus from inception to present for studies comparing generalist-led hospital models with traditional specialist-led or other models. Observational studies and randomised trials will be included. The primary outcomes are patient mortality, morbidity, satisfaction, healthcare costs, length of stay, readmissions and consultations. Two reviewers will independently screen studies, extract data and assess quality using the Newcastle-Ottawa Scale for observational studies and the Cochrane Risk of Bias tool for randomised trials. A narrative synthesis will be conducted, with a meta-analysis if appropriate. Grading of Recommendations Assessment, Development and Evaluation will assess certainty of evidence. Heterogeneity will be explored through subgroup analyses and meta-regression. The review will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. ETHICS AND DISSEMINATION: Ethical approval is not required as this is a protocol for a systematic review with no primary data collection. The results will be disseminated through a peer-reviewed publication, conference presentations and stakeholder engagement activities. PROSPERO REGISTRATION NUMBER: CRD42024600155.
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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 | 0.086 | 0.083 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.017 | 0.015 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.084 | 0.014 |
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".