Effects of medical scribes on patients, physicians, and safety: A scoping review
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
A scoping review was conducted to investigate the effects of medical scribes on physician and patient satisfaction, physician burnout, the educational experience of medical students and residents, risk, and safety. The databases PubMed, EMBASE, and CINAHL were searched for the years 2000-2020. Relevant studies were analyzed qualitatively. Literature analysis found that medical scribes increase physician satisfaction and decrease physician burnout, while having minimal impact on patient satisfaction. Patient impressions of scribes tend to be neutral to positive. The effects of scribes on medical student and resident education appear positive in preliminary results. Scribe-generated notes seem to be of equal or greater quality compared to physician-generated notes, though few studies have examined this issue. The impact of scribes on risk and safety has not been fully studied. Few studies of medical scribes have been conducted in Canada, and only one has been published in a peer-reviewed journal. Medical scribes are a promising solution to the growing challenge of physician documentation-related burden fueled by electronic health records and electronic medical records. Studies on the impact of scribes in countries other than the United States are needed. Administrative hurdles to the implementation of scribes in Canadian hospitals could be a barrier to pilot studies in Canada.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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