Differences in Acute Ischemic Stroke Quality of Care and Outcomes by Primary Stroke Center Certification Organization
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Primary stroke center (PSC) certification was established to identify hospitals providing evidence-based care for stroke patients. The numbers of PSCs certified by Joint Commission (JC), Healthcare Facilities Accreditation Program, Det Norske Veritas, and State-based agencies have significantly increased in the past decade. This study aimed to evaluate whether PSCs certified by different organizations have similar quality of care and in-hospital outcomes. METHODS: The study population consisted of acute ischemic stroke patients who were admitted to PSCs participating in Get With The Guidelines-Stroke between January 1, 2010, and December 31, 2012. Measures of care quality and outcomes were compared among the 4 different PSC certifications. RESULTS: A total of 477 297 acute ischemic stroke admissions were identified from 977 certified PSCs (73.8% JC, 3.7% Det Norske Veritas, 1.2% Healthcare Facilities Accreditation Program, and 21.3% State-based). Composite care quality was generally similar among the 4 groups of hospitals, although State-based PSCs underperformed JC PSCs in a few key measures, including intravenous tissue-type plasminogen activator use. The rates of tissue-type plasminogen activator use were higher in JC and Det Norske Veritas (9.0% and 9.8%) and lower in State and Healthcare Facilities Accreditation Program certified hospitals (7.1% and 5.9%) (P<0.0001). Door-to-needle times were significantly longer in Healthcare Facilities Accreditation Program hospitals. State PSCs had higher in-hospital risk-adjusted mortality (odds ratio 1.23, 95% confidence intervals 1.07-1.41) compared with JC PSCs. CONCLUSIONS: Among Get With The Guidelines-Stroke hospitals with PSC certification, acute ischemic stroke quality of care and outcomes may differ according to which organization provided certification. These findings may have important implications for further improving systems of care.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".