Reliability of Patient-Report, Physician-Report, and Medical Record Review to Identify Hospital-Acquired Complications
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
This prospective study of internal medicine inpatients treated at 2 hospitals in Toronto, Canada, between September 1, 2016, and September 1, 2017, compared patient-report, physician-report, and detailed medical record review to identify specific hospital-acquired complications. Six complications were assessed: delirium, catheter-associated urinary tract infection, acute kidney injury, deep vein thrombosis/pulmonary embolism, hospital-acquired pneumonia, or fall. The study included 207 patients and physician responses were obtained for 156 (75%). Complications were identified in 28 (14%) patients by medical record review, 30 (14%) patients by patient-report, and 11 (7%) patients by physician-report. Fifty-four (26%) patients experienced a complication as identified through at least one of the 3 methods. There was little agreement between the 3 methods (Fleiss' ĸ 0.15, P < 0.001). All 3 sources agreed on the occurrence of a specific complication in only 1 patient (1%). Multiple approaches likely are needed to adequately measure hospital-acquired complications.
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 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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