Resident and Attending Physicians’ Perceptions of Patient Access to Provider Notes: Comparison of Perceptions Prior to Pilot Implementation
Bibliographic record
Abstract
BACKGROUND: As electronic health records have become a more integral part of a physician's daily life, new electronic health record tools will continue to be rolled out to trainees. Patient access to provider notes is becoming a more widespread practice because this has been shown to increase patient empowerment. OBJECTIVE: In this analysis, we compared differences between resident and attending physicians' perceptions prior to implementation of patient access to provider notes to facilitate optimal use of electronic health record features and as a potential for patient empowerment. METHODS: This was a single-site study within an academic internal medicine program. Prior to implementation of patient access to provider notes, we surveyed resident and attending physicians to assess differences in perceptions of this new electronic health record tool using an open access survey provided by OpenNotes. RESULTS: We surveyed 37% (20/54 total) of resident physicians and obtained a 100% response rate and 72% (31/44 total) of attending physicians. Similarities between the groups included concerns about documenting sensitive topics and anticipation of improved patient engagement. Compared with attending physicians, resident physicians were more concerned about litigation, discussing weight, offending patients, and communicated less overall with patients through electronic health record. CONCLUSIONS: Patient access to provider notes has the potential to empower patients but concerns of the resident physicians need to be validated and addressed prior to its utilization.
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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".