Can reflective multicriteria be the new paradigm for healthcare decision-making? The EVIDEM journey
Bibliographic record
Abstract
BACKGROUND: Multiple technologies, procedures and programs call for fairly-based decisions for prioritization of healthcare interventions. There is a diversity of perspectives of what constitutes a legitimate decision, which depends on both the process and the reasoning applied. Current approaches focus on technical aspects while methods to support alignment of decisions with the compassionate impetus of healthcare systems is lacking. METHODS: The framework was developed based on an analysis of the foundations of healthcare systems, the reasoning underlying decisions and fair processes. The concept of reflective multicriteria was created: it assumes that decisionmakers guided by a generic interpretative frame rooted in the compassionate impetus of healthcare systems, can sharpen their reasoning, raise awareness of their motivation and increase legitimacy of decisions. The initial framework was made available through a not for profit organization (the EVIDEM Collaboration, 2006-2017) to stimulate its development with thought leaders and stakeholders in an open source philosophy. Development was tailored to the real-life needs of decisionmakers and drew on several domains of knowledge including healthcare ethics, evidenced-based medicine, health economics, health technology assessment and multicriteria approaches. RESULTS: The 10th edition framework builds on four dimensions: (1) the universal impetus of healthcare systems, (2) reasoning, values and ethics, (3) evidence and knowledge on interventions, and (4) a transformative process. Mathematical aspects of the framework are designed to help clarify, express and share individual reasoning; this non-conventional use of numbers requires a cultural change and needs to be phased in slowly. The framework includes four tools for easy adaptation and operationalization: (a) concepts and operationalization, (b) adapt and pilot, (c) evidence matrix, (d) mathematical representation of reasoning. Application is useful throughout all types of healthcare interventions, for all levels of decision, and across the globe. CONCLUSION: By clarifying their reasoning while keeping decisionmakers aware of the impetus of healthcare systems, reflective multicriteria provides an effective approach to increase the legitimacy of decisions. Beyond a tool, reflective multicriteria pioneered by EVIDEM is geared to transform our vision of the value of healthcare interventions and how they might contribute to relevant, equitable and sustainable 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 | 0.176 | 0.175 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.088 |
| Scholarly communication | 0.023 | 0.035 |
| Open science | 0.006 | 0.019 |
| Research integrity | 0.013 | 0.022 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".