Engaging citizens in the development of a health system performance assessment framework: a case study in Ireland
Bibliographic record
Abstract
BACKGROUND: The launch in 2017 of the Irish 10-year reform programme Sláintecare represents a key commitment in the future of the health system. An important component of the programme was the development of a health system performance assessment (HSPA) framework. In 2019, the Department of Health of Ireland (DoH) and Health Service Executive (HSE) commissioned the technical support of researchers to develop an outcome-oriented HSPA framework which should reflect the shared priorities of multiple stakeholders, including citizens. This study describes the method applied in the Irish context and reflects on the added value of using a citizen panel in the development of an HSPA framework. METHODS: A panel of 15 citizens was convened, recruited by a third-party company using a sampling strategy to achieve a balanced mix representing the Irish society. Panellists received lay-language preparatory materials before the meeting. Panellists used a three-colour scheme to signal the importance of performance measures. An exit questionnaire was administered to understand how participants experienced being part of the panel. The citizen panel was the first in a series of three panels towards the development of the HSPA framework, followed by panels including representatives of the DoH and HSE, and representatives from professional associations and special interest groups. RESULTS: The citizen panel generated 249 health performance measures ranging across 13 domains. Top-ranking domains to the citizen panel (people-centredness, coordination of care, and coverage) were less prioritized by the other panels; domains less prioritized by the citizen panel, such as accessibility, responsiveness, efficiency, and effectiveness, were of higher priority in the other panels. Citizen panellists shared a similar understanding of what a citizen panel involves and described their experience at the panel as enjoyable, interesting, and informative. CONCLUSIONS: The priorities of the citizen panel were accounted for during all phases of developing the HSPA framework. This was possible by adopting an inclusive development process and by engaging citizens early on. Citizen engagement in HSPA development is essential for realizing citizen-driven healthcare system performance and generating trust and ownership in performance intelligence. Future research could expand the use of citizen panels to assess, monitor, and report on the performance of healthcare systems.
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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 | 0.058 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".