Quality of acute stroke care in Korea (2008–2014): Retrospective analysis of the nationwide and nonselective data for quality of acute stroke care
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Background There is limited information about non-selective and contemporary data on quality of stroke care and its variation among hospitals at a national level. Patients and methods We analysed data of the patients admitted to 258 acute stroke care hospitals covering the entire country from the Acute Stroke Quality Assessment Program, which was performed by the Health Insurance Review and Assessment Service from 2008 to 2014 in South Korea. The primary outcome measure was defect-free stroke care (all-or-none), based on six get with the guidelines-stroke performance measures (except venous thromboembolism prophylaxis). Results Among 43,793 acute stroke patients (mean age, 67 ± 14 years; male, 55%), 31,915 (72.9%) were hospitalised due to ischaemic stroke. At a patient level, defect-free stroke care steadily increased throughout the study period (2008, 80.2% vs. 2014, 92.1%), but there were large disparities among hospitals (mean = 50.7%, SD = 21.7%). Defect-free stroke care was given more frequently in patients being treated in hospitals with 25 or more stroke cases per month (odds ratio [OR] 2.83; 95% confidence interval [CI] 1.69–4.72), delivery of intravenous thrombolysis one or more times per month (OR 2.37; 95% CI 1.44–3.92), or provision of stroke unit care (OR 1.75; 95% CI 1.22–2.52). Discussion This study shows that the quality of stroke care in Korea is improving over time and is higher in centres with a larger volume of stroke or intravenous thrombolysis cases and providing stroke unit care but hospital disparities exist. Conclusion Reducing large differences in defect-free stroke care among acute stroke care hospitals should be continuously pursued.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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