RESUMO
OBJECTIVES: Accreditation in France relies on a mandatory 4-year cycle of self-assessment and a peer review of 82 standards, among which 14 focus priority standards (FPS). Hospitals are also required to measure yearly quality indicators (QIs-5 in 2010). On advice given by the accreditation committee of HAS (Haute Autorité en Santé), based on surveyors proposals and relying mostly on compliance to standards, accreditation decisions are taken by the board of HAS. Accreditation is still perceived by hospitals as a burdensome process and a simplification would be welcomed. The hypothesis was that a more limited number of criteria might give sufficient amount of information on hospitals overall quality level, appraised today by accreditation decisions. DESIGN: The accuracy of predictions of accreditation decisions given by a model, Partial Least Square-2 Discriminant Analysis (PLS2-DA), using only the results of FPS and QIs was measured. Accreditation decisions (full accreditation (A), recommendations or reservation (B), remit decision or non-accreditation (C)), results of FPS and QIs were considered qualitative variables. Stability was assessed by leave one out cross validation (LOOCV). SETTING AND PARTICIPANTS: All French 489 acute care organisations (ACO) accredited between June 2010 and January 2012 were considered, 304 of them having a rehabilitation care sector (RCS). RESULTS: Accuracy of prediction of accreditation decisions was good (89% of ACOs and 91% of ACO-RCS well classified). Stability of results appeared satisfactory when using LOOCV (87% of ACOs and 89% of ACO-RCS well classified). Identification of worse hospitals was correct (90% of ACOs and 97% of ACO-RCS predicted C were actually C). CONCLUSIONS: Using PLS2-DA with a limited number of criteria (QIs and FPS) provides an accurate prediction of accreditation decisions, especially for underperforming hospitals. This could support accreditation committees which give advices on accreditation decisions, and allow fast-track handling of 'safe' reports.
RESUMO
BACKGROUND: In acute myocardial infarction, the relationship between volume and quality indicators (QIs) is poorly documented. Through a nationwide assessment of QIs at discharge repeated for 3 years, we aimed to quantify the relationship between volume and QIs in survivors after acute myocardial infarction. METHODS AND RESULTS: Almost all healthcare centers in France participated. Medical records were randomly selected. Data collection was performed by an independent group. QIs for acute myocardial infarction were defined by an expert consensus group as appropriate prescription at discharge of aspirin, clopidogrel, ß-blocker, statin, and an angiotensin-converting enzyme inhibitor in patients with left ventricular ejection fraction <0.40. A composite QI was calculated through the use of the all-or-none method. Volume was classified into 7 categories based on the number of admissions for acute myocardial infarctions in 2008 (centers with <10 acute myocardial infarctions were excluded). Odds ratios adjusted for age and sex with 95% confidence interval for volume categories were calculated by use of logistic regression for each QI. Temporal changes were tested in centers that participated in all 3 campaigns. A total of 46 390 records were examined: 18 159 in 2008, 12 837 in 2009, and 15 394 in 2010. Two hundred ninety-one centers were eligible for the temporal analysis. There was a significant increase between 2008 and 2009 in appropriate prescription of antiplatelet agents, ß-blockers, angiotensin-converting enzyme inhibitor, statins at discharge, and the composite indicator. Similarly, a significant increase was observed between 2009 and 2010 in appropriate prescription of angiotensin-converting enzyme inhibitor and ß-blockers and in the composite QI. Compared with a volume of >300, a significantly lower rate of all QIs was observed in centers with the lowest volume. Odds ratios progressively decreased with increasing volume. Despite a significant increase in the composite QI over the 3 years, a significant relationship persisted between volume and quality of care. CONCLUSIONS: Analysis of QIs at discharge demonstrates the existence of a relationship between volume and appropriate prescriptions at discharge. Centers with the highest volume perform better on quality measures than centers with lower volumes. Temporal analysis over 3 consecutive years confirms this relationship and shows that it persists despite improvement in QIs between 2008 and 2010.
