Shorter Door-to-Balloon Time in ST-Elevation Myocardial Infarction Saves Insurance Payments: A Single Hospital Experience in Taiwan.
Bibliographic record
Abstract
BACKGROUND: The relationship between quality of care and cost of medical services is a popular topic. In this study, we examined whether a reduced door-to-balloon (D2B) time led to cost savings, benefitted insurance payers, and improved patient outcomes. METHODS: We retrospectively enrolled consecutive patients who presented with ST-segment elevation myocardial infarction (STEMI) and received primary percutaneous coronary intervention (PCI) between Feb. 1, 2007, and Jul. 31, 2009, at a tertiary hospital in Taiwan. The patient data were collected by chart review. We utilized claims data from the hospital financial system as the proxy for insurance payer costs. We only included the claims data, regardless of whether patients were inpatients or outpatients, associated with the first three cardiovascular related ICD-9 codes. Multivariable logistic regression was used to examine the relationships between the D2B time, in-hospital mortality and one-year cardiovascular readmission. We utilized a multivariable linear regression to test the relationships between the D2B time, hospitalization cost and one-year cardiovascular-related cost. RESULTS: The D2B time did not influence the in-hospital mortality rate, but a D2B time greater than 90 min increased the probability of one-year cardiovascular readmission (p = 0.018). The D2B time did not increase the index hospitalization cost, but patients with a D2B time above 90 min had 14.6% higher one-year cardiovascular- related costs. CONCLUSIONS: Our study shows that the D2B time in patients with STEMI could impact the one-year cardiovascular readmission and one-year cardiovascular-related health cost. These results suggest that the pursuit of high-quality care not only leads to better outcomes, but also reduces costs. KEY WORDS: Acute myocardial infarction; Cost; Door-to-balloon time; Insurance payer; Quality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".