Themes for evaluating the quality of initiatives to engage patients and family caregivers in decision-making in healthcare systems: a scoping review
Bibliographic record
Abstract
OBJECTIVE: To identify the key themes for evaluating the quality of initiatives to engage patients and family caregivers in decision-making across the organisation and system domains of healthcare systems. METHODS: We conducted a scoping review. Seven databases of journal articles were searched from their inception to June 2019. Eligible articles were literature reviews published in English and provided useful information for determining aspects of engaging patients and family caregivers in decision-making to evaluate. We extracted text under three predetermined categories: structure, process and outcomes that were adapted from the Donabedian conceptual framework. These excerpts were then independently open-coded among four researchers. The subsequent themes and their corresponding excerpts were summarised to provide a rich description of each theme. RESULTS: Of 7747 unique articles identified, 366 were potentially relevant, from which we selected the 42 literature reviews. 18 unique themes were identified across the three predetermined categories. There were six structure themes: engagement plan, level of engagement, time and timing of engagement, format and composition, commitment to support and environment. There were four process themes: objectives, engagement approach, communication and engagement activities. There were eight outcome themes: decision-making process, stakeholder relationship, capacity development, stakeholder experience, shape policy/service/programme, health status, healthcare quality, and cost-effectiveness. CONCLUSIONS: The 18 themes and their descriptions provide a foundation for identifying constructs and selecting measures to evaluate the quality of initiatives for engaging patients and family caregivers in healthcare system decision-making within the organisation and system domains. The themes can be used to investigate the mechanisms through which relevant initiatives are effective and investigate their effectiveness.
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 | 0.173 | 0.328 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.050 | 0.042 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".