A Standard Set of Value-Based Patient-Centered Outcomes and Measures of Overall Health in Adults
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The definition of population-specific outcomes is an essential precondition for the implementation of value-based health care. We developed a minimum standard outcome set for overall adult health (OAH) to facilitate the implementation of value-based health care in tracking, comparing, and improving overall health care outcomes of adults across multiple conditions, which would be of particular relevance for primary care and public health populations. METHODS: The International Consortium for Health Outcomes Measurement (ICHOM) convened an international panel (patients, clinicians, and topic experts). Following the development of a conceptual framework, a modified Delphi method (supported by public consultations) was implemented to identify, in sequence, the relevant domains, the best instruments for measuring them, the timing of measurement, and the relevant adjustment variables. FINDINGS: Outcomes were identified in relation to overall health status and the domains of physical, mental, and social health. Three instruments covering these domains were identified: PROMIS Scale v1.2-Global Health (10 items), WHO Wellbeing Index (5 items), and the WHO Disability Assessment Schedule 2.0 (12 items). Case-mix variables included a range of sociodemographic and biometric measures. Yearly measurement was proposed for all outcomes and most case-mix variables. INTERPRETATION: The ICHOM OAH Standard Set has been developed through consensus-based methods based on predefined criteria following high standards for the identification and selection of high-quality measures The involvements of a wide range of stakeholders supports the acceptability of the set, which is readily available for use and feasibility testing in clinical settings.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it