Assessment of the incidence and preventability of adverse events in hospitals: an integrative 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
OBJECTIVE: To highlight the scientific production related to the use of the retrospective chart review methods to assess the incidence and preventability of adverse events in hospitals. METHOD: An integrative review in the MEDLINE, LILACS, SCOPUS, Web of Science and EMBASE databases conducted in May 2019 with the following guiding question: What is known about the retrospective chart review methods to assess the incidence and preventability of adverse events in hospitals? Subsequently, the categorization, synthesis, and classification of the evidence levels of the included publications were performed. RESULTS: In the 13 selected studies, the instruments adopted to assess the occurrence of adverse events were the Harvard Medical Practice Study, the Canadian Adverse Event Study, the Quality in Australian Health Care Study, and the Global Trigger Tool. Incidence ranged from 5.7 to 14.2%, while preventability ranged from 31 to 83%. CONCLUSION: Differences in incidence and preventability were found, showing different results in the quality of care provided, the information registered in medical records, the screening criteria used, and the assessments of the reviewers.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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