In-hospital Mortality Due to Acute Myocardial Infarction. Relevance of Type of Hospital and Care Provided. RECALCAR Study
ABSTRACT To investigate the relationship between in-hospital mortality due to acute myocardial infarction and type of hospital, discharge service, and treatment provided.
Retrospective analysis of 100 993 hospital discharges with a principal diagnosis of myocardial infarction in hospitals of the Spanish National Health Service. In-hospital mortality was adjusted for risk following the models of the Institute for Clinical Evaluative Sciences (Canada) and the Centers for Medicare & Medicaid Services (United States).
Hospital characteristics are relevant to explain the variation in the individual probability of dying from myocardial infarction (median odds ratio: 1.3561). The risk-adjusted in-hospital mortality in cluster 3 and especially in cluster 4 hospitals (500 beds to 1000 beds and medium-high complexity) was significantly lower than in hospitals with less than 200 beds. Cluster 5 (more than 1000 beds), which includes a diverse group of hospitals, had a higher mortality rate than clusters 3 and 4. The adjusted mortality in the groups with the best and worst outcomes was 6.74% (cluster 4) and 8.49% (cluster 1), respectively. Mortality was also lower when the cardiology unit was responsible for the discharge or when angioplasty had been performed.
The typology of the hospital, treatment in a cardiology unit, and percutaneous coronary intervention are significantly associated with the survival of a patient hospitalized for myocardial infarction. We recommend that the Spanish National Health Service establish health care networks that favor percutaneous coronary intervention and the participation of cardiology units in the management of patients with acute myocardial infarction. Full English text available from:www.revespcardiol.org/en.
- New England Journal of Medicine 12/1997; 337(19):1360-9. DOI:10.1056/NEJM199711063371906 · 54.42 Impact Factor
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ABSTRACT: Despite decades of efforts to improve quality of health care, poor performance persists in many aspects of care. Less than 1% of the enormous national investment in medical research is focused on improving health care delivery. Furthermore, when effective innovations in clinical care are discovered, uptake of these innovations is often delayed and incomplete. In this paper, we build on the established principle of 'positive deviance' to propose an approach to identifying practices that improve health care quality. We synthesize existing literature on positive deviance, describe major alternative approaches, propose benefits and limitations of a positive deviance approach for research directed toward improving quality of health care, and describe an application of this approach in improving hospital care for patients with acute myocardial infarction. The positive deviance approach, as adapted for use in health care, presumes that the knowledge about 'what works' is available in existing organizations that demonstrate consistently exceptional performance. Steps in this approach: identify 'positive deviants,' i.e., organizations that consistently demonstrate exceptionally high performance in the area of interest (e.g., proper medication use, timeliness of care); study the organizations in-depth using qualitative methods to generate hypotheses about practices that allow organizations to achieve top performance; test hypotheses statistically in larger, representative samples of organizations; and work in partnership with key stakeholders, including potential adopters, to disseminate the evidence about newly characterized best practices. The approach is particularly appropriate in situations where organizations can be ranked reliably based on valid performance measures, where there is substantial natural variation in performance within an industry, when openness about practices to achieve exceptional performance exists, and where there is an engaged constituency to promote uptake of discovered practices. The identification and examination of health care organizations that demonstrate positive deviance provides an opportunity to characterize and disseminate strategies for improving quality.Implementation Science 06/2009; 4:25. DOI:10.1186/1748-5908-4-25 · 3.47 Impact Factor