Impact of new health care policies on the quality of acute myocardial infarction treatment in Swiss hospitals: A before and after observational study
Bibliographic record
Abstract
Objective: Following a revision of the Swiss Federal Health Insurance Act, the regional hospital planning structure was modified and the hospital financing organized at a national level with the use of diagnosis related groups (SwissDRGs). The aim of this observational study was to determine in an independent way the initial impact of these changes on the quality of hospital treatment, with patients hospitalized for Acute Myocardial Infarction (AMI) being the chosen study group.Methods: We used prospective data from a Swiss clinical registry for AMI. The quality was measured based on the adherence to 10 evidence-based performance indicators for AMI treatment, and on the evaluation of in-hospital outcomes (mortality, complications, length of hospital stay [LOS]) globally and for seven pre-defined vulnerable subgroups. The study compared patient-based data before (2011) and after (2012) the implementation of the reform.Results: The study included 33 matched hospitals, and compared the AMI treatment of 2,491 patients in 2011 (before) and 2,544 in 2012 (after the hospital reform). No significant changes in the evidence-based performance indicators were observed, but an on average one day reduction in the LOS and worse outcomes in one of the pre-defined group of patients were found. The issue of how the clinical team achieved these results was not directly explored due to the underlying registry’s unalterable structure.Conclusions: One year after the implementation of a new hospital financing system in Switzerland, the quality of treatment delivered to patients hospitalized for AMI was maintained overall. The worse in-hospital mortality in one pre-defined vulnerable subgroup could reflect the emergence of difficulties for clinical teams to cope with patients demanding extra care and time. Further investigation is warranted.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".