Chart documentation quality and its relationship to the validity of administrative data discharge records
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
The validity of administrative data may be vulnerable to how well physicians document medical charts. The objective of this study is to determine the relationship between chart documentation quality and the validity of administrative data. The charts for patients who underwent carotid endarterectomy were re-abstracted and rated for the quality of documentation. Poorly and well-documented charts were compared by patient, physician, and hospital variables, as well as on agreement between the administrative and re-abstracted data. Of the 2061 charts reviewed, 42.6 per cent were rated well documented. The proportion of charts well documented varied from 14.6 to 87.5 per cent across 17 hospitals, but did not vary significantly by patient characteristics. The kappa statistic was generally higher for well-documented charts than for poorly documented charts, but varied across comorbidities. In conclusion, poorly documented hospital charts tend to be translated into invalid administrative data, which reduces the communication of clinical information among healthcare providers.
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 | 0.019 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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