Shared-Care in Complex Malignant Hematology: An Integrative Review Using the RE-AIM Evaluation Framework
Bibliographic record
Abstract
Complex malignant hematology (CMH) shared-care programs have been established to support patients with access to care closer to home. This integrative review examined what is known about CMH shared-care using the RE-AIM evaluation framework. We searched five electronic databases for articles published until 16 January 2024. Articles were included if they were qualitative or quantitative studies, reviews or discussion papers, and reported on an experience with shared-care (defined as a reciprocal, ongoing patient-sharing relationship between a specialist centre and community hospital) for patients with hematological malignancies, and examined one or more aspects of the RE-AIM framework. The search yielded 6523 articles; 10 articles describing eight shared-care experiences. Indicators of reach were reported for 65% of the programs, and emphasized some patient eligibility criteria. Effectiveness indicators were reported for 28% of programs, and suggested favourable survival outcomes within a shared-care model; however, health system impact and quality of life studies were lacking. Indicators of adoption and implementation were reported for 56% and 42% of programs, respectively, and emphasized multidisciplinary teams, infrastructure support, and communication strategies. Maintenance was not reported. Common elements contribute to the implementation of existing CMH shared-care programs; however, a formal evaluation remains an area of need.
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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 | 0.021 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".