Bibliographic record
Abstract
Access to Personal Health Information (PHI) is a valuable part of the modern health care model. Timely access to relevant PHI assists care providers in making clinical decisions and ensure that patients receive the highest quality of care. PHI is highly sensitive and unauthorized disclosure of PHI has potential to lead to social, economic, or even physical harm to the patient. Traditional electronic health (eHealth) tools are designed for the needs of care providers and are insufficient for the needs of patients. Our research goal is to investigate the requirements of electronic health care systems which place patient health and privacy above all other concerns. Control of secure resources is a well established area of research in which many techniques such as cryptography, access control, authentication, and organizational policy can be combined to maintain the confidentiality and integrity of data. Access control is the dominant data owner facing privacy control. To better understand this domain we conducted a scoping literature review to rapidly map the key concepts underpinning patient facing access controls in eHealth systems. We present the analysis of that corpus as well as a set of identified requirements. Based on the identified requirements we developed Circle of Health based Access Control (CoHBAC), a patient centered access control model. We then performed a second scoping review to extend our research beyond just access controls, which are insufficient to provide reasonable privacy alone. The second review yielded a larger, more comprehensive, set of sixty five requirements for patient centered privacy systems. We refined CoHBAC into Privacy Centered Access Control (PCAC) to meet the needs of our second set of requirements. Using the conceptual model of accountability that emerged from the reviewed literature we present the identified requirements organized into the Patient Centered Privacy Framework. We applied our framework to the Canadian health care context to demonstrate its applicability.
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 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 | 0.048 | 0.133 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.008 | 0.016 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".