Accountable priority setting for trust in health systems - the need for research into a new approach for strengthening sustainable health action in developing countries
Bibliographic record
Abstract
Despite multiple efforts to strengthen health systems in low and middle income countries, intended sustainable improvements in health outcomes have not been shown. To date most priority setting initiatives in health systems have mainly focused on technical approaches involving information derived from burden of disease statistics, cost effectiveness analysis, and published clinical trials. However, priority setting involves value-laden choices and these technical approaches do not equip decision-makers to address a broader range of relevant values - such as trust, equity, accountability and fairness - that are of concern to other partners and, not least, the populations concerned. A new focus for priority setting is needed.Accountability for Reasonableness (AFR) is an explicit ethical framework for legitimate and fair priority setting that provides guidance for decision-makers who must identify and consider the full range of relevant values. AFR consists of four conditions: i) relevance to the local setting, decided by agreed criteria; ii) publicizing priority-setting decisions and the reasons behind them; iii) the establishment of revisions/appeal mechanisms for challenging and revising decisions; iv) the provision of leadership to ensure that the first three conditions are met.REACT - "REsponse to ACcountable priority setting for Trust in health systems" is an EU-funded five-year intervention study started in 2006, which is testing the application and effects of the AFR approach in one district each in Kenya, Tanzania and Zambia. The objectives of REACT are to describe and evaluate district-level priority setting, to develop and implement improvement strategies guided by AFR and to measure their effect on quality, equity and trust indicators. Effects are monitored within selected disease and programme interventions and services and within human resources and health systems management. Qualitative and quantitative methods are being applied in an action research framework to examine the potential of AFR to support sustainable improvements to health systems performance.This paper reports on the project design and progress and argues that there is a high need for research into legitimate and fair priority setting to improve the knowledge base for achieving sustainable improvements in health outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.391 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".