Disclosing Adverse Events to Patients: International Norms and Trends
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
OBJECTIVES: There is a growing expectation in health systems around the world that patients will be fully informed when adverse events occur. However, current disclosure practices often fall short of this expectation. METHODS: We reviewed trends in policy and practice in 5 countries with extensive experience with adverse event disclosure: the United States, the United Kingdom, Canada, New Zealand, and Australia. RESULTS: We identified 5 themes that reflect key challenges to disclosure: (1) the challenge of putting policy into large-scale practice, (2) the conflict between patient safety theory and patient expectations, (3) the conflict between legal privilege for quality improvement and open disclosure, (4) the challenge of aligning open disclosure with liability compensation, and (5) the challenge of measurement related to disclosure. CONCLUSIONS: Potential solutions include health worker education coupled with incentives to embed policy into practice, better communication about approaches beyond the punitive, legislation that allows both disclosure to patients and quality improvement protection for institutions, apology protection for providers, comprehensive disclosure programs that include patient compensation, delinking of patient compensation from regulatory scrutiny of disclosing physicians, legal and contractual requirements for disclosure, and better measurement of its occurrence and quality. A longer-term solution involves educating the public and health care workers about patient safety.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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