Bibliographic record
Abstract
BACKGROUND: Developments in information technology promise to revolutionise the delivery of health care by providing access to data in a timely and efficient way. Information technology also raises several important concerns about the confidentiality and privacy of health data. New and existing legislation in Europe and North America may make access to patient level data difficult with consequent impact on research and health surveillance. Although research is being conducted on technical solutions to protect the privacy of personal health information, there is very little research on ways to improve individuals power over their health information. This paper proposes a health care information directive, analogous to an advance directive, to facilitate choices regarding health information disclosure. RESULTS AND DISCUSSION: A health care information directive is described which creates a decision matrix that combines the ethical appropriateness of the use of personal health information with the sensitivity of the data. It creates a range of possibilities with in which individuals can choose to contribute health information with or without consent, or not to contribute information at all. CONCLUSION: The health care information directive may increase individuals understanding of the uses of health information and increase their willingness to contribute certain kinds of health information. Further refinement and evaluation of the directive is required.
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.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".