Tools and instruments to implement value-based healthcare in hospital settings: A scoping review protocol
Bibliographic record
Abstract
Abstract This protocol details our process for a systematic scoping review to collect the overall evidence on defined methods and tools for implementation of value-based healthcare within hospital settings. A search strategy based on the intersection of value-based healthcare and tools/methodologies will be used to search PubMed, EMBASE [OVID], and ISI Web of Knowledge. Two independent researchers will screen titles and abstracts for inclusion/exclusion criteria, followed by full texts; disagreements will be resolved by a third researcher and consensus. We will extract the following categories of data, if available and applicable: publication details, study characteristics, and conceptualization of value-based healthcare. Results will be presented narratively and visually and distilled to inform evidence-based value-based healthcare implementation recommendations for hospitals. Keywords Value-based health care; hospitals; implementation; healthcare delivery; outcomes measurement; patient-reported outcomes
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 | 0.254 | 0.198 |
| Meta-epidemiology (narrow) | 0.005 | 0.008 |
| Meta-epidemiology (broad) | 0.010 | 0.014 |
| Bibliometrics | 0.023 | 0.019 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.086 | 0.026 |
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".