Patients and Health Care Providers' Concerns about the Privacy of Electronic Health Records: A Review of the Literature
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
Topic area: Patients and Health Care Providers' Concerns about the security of Electronic Health Records. Background: Electronic Health Records hold the potential for great improvements in healthcare provision yet take-up in North American remains slow behind Australia and Europe. We believe that one of the reasons for this is the lack of attention to privacy concerns. Method: A structured literature review was undertaken to identify the current state of knowledge concerning patients and health care provider's perspectives on privacy and the EHR. 21 papers were ultimately identified and are summarized here. Results: Two main themes were identified: General concerns with the security of EHRs and specific concerns regarding sharing information within EHRs. Discussion: In general patients were less concerned with the privacy and security of their personal health information within EHRs than their HCPs were. However, this leaves an interesting conundrum for us to consider: Do we have a duty to protect patients even from themselves with regards to the sharing of their personal health information?
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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