Clinical Documentation in an Era of Increasing Transparency: The Impact of Electronic Portals on Care
Bibliographic record
Abstract
Electronic health records (EHRs) and consumer health portals have implications for improving the quality and cost-effectiveness of healthcare and make it much easier for patients and families to access health information in a timely and convenient manner. However, the accessibility of information afforded by EHRs and health portals changes the dynamic of control over health information in very significant ways. Institutions and their clinicians have typically been the caretakers of these documents; therefore, the introduction of portals represents a major cultural shift in healthcare. The efforts of both clinicians and patients are needed to effectively make this shift, as the implementation of new technology is uniquely challenging within a healthcare setting. An interactive workshop was facilitated to understand clinicians' perceived challenges of this shift with a specific focus on the implications of increased transparency and patients' increased access to health information.
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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 | 0.061 | 0.113 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".