Restoring Core Values: An International Charter for Human Values in Healthcare
Bibliographic record
Abstract
Background: The human dimensions of healthcare are fundamental to the practice of compassionate, safe, and ethical relationship-centered care. Attending to the human dimensions improves patient and clinician satisfaction, outcomes and quality of care; however, these dimensions have not received the emphasis necessary to make them central to every healthcare encounter. We established an international collaborative effort to identify and promote the human dimensions of care.Objectives: a) To describe work to date on the International Charter for Human Values in Healthcare; b) To discuss translation of the Charter’s universal values into education, research, and practice.Methods: An international working group of expert educators, clinicians, linguists, and researchers identified initial values that should be present in every healthcare interaction. The working group and four additional groups -- National Academies of Practice (NAP) USA, International Conference on Communication in Healthcare, Interprofessional Patient-Centered Care Conference, American Academy on Communication in Healthcare Forum -- identified values for all healthcare interactions and prioritized top values. The NAP group also prioritized top values for interprofessional interactions. Additional data was gathered via a Delphi process and 2 focus groups of Harvard Macy Institute scholars and faculty.Results: Through iterative content analyses and consensus, we identified 5 categories of core human values that should be present in every healthcare interaction: Capacity for Compassion, Respect for Persons, Commitment to Integrity and Ethical Practice, Commitment to Excellence, and Justice in Healthcare. Through further consensus and Delphi methodology, we identified values within each category.Conclusions: The International Charter for Human Values in Healthcare [1] is a cooperative effort to restore core human values to healthcare around the world. Major healthcare and education partners have joined this international effort. We are working to develop methods to translate the Charter’s universal values into education (teaching, assessment, curricula), research and practice.ReferenceThe International Charter for Human Values in Healthcare. http://charterforhealthcarevalues.org
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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 | 0.096 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.009 | 0.034 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.014 |
| 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".