title: Short Term Survival after Admission for Heart Failure in Sweden: Applying Multilevel Analyses of Discriminatory Accuracy to Evaluate Institutional Performance.
abstract: BACKGROUND
  Hospital performance is frequently evaluated by analyzing differences between hospital averages in some quality indicators. The results are often expressed as quality charts of hospital variance (e.g., league tables, funnel plots). However, those analyses seldom consider patients heterogeneity around averages, which is of fundamental relevance for a correct evaluation. Therefore, we apply an innovative methodology based on measures of components of variance and discriminatory accuracy to analyze 30-day mortality after hospital discharge with a diagnosis of Heart Failure (HF) in Sweden.
  
  
  METHODS
  We analyzed 36,943 patients aged 45-80 treated in 565 wards at 71 hospitals during 2007-2009. We applied single and multilevel logistic regression analyses to calculate the odds ratios and the area under the receiver-operating characteristic (AUC). We evaluated general hospital and ward effects by quantifying the intra-class correlation coefficient (ICC) and the increment in the AUC obtained by adding random effects in a multilevel regression analysis (MLRA). Finally, the Odds Ratios (ORs) for specific ward and hospital characteristics were interpreted jointly with the proportional change in variance (PCV) and the proportion of ORs in the opposite direction (POOR).
  
  
  RESULTS
  Overall, the average 30-day mortality was 9%. Using only patient information on age and previous hospitalizations for different diseases we obtained an AUC = 0.727. This value was almost unchanged when adding sex, country of birth as well as hospitals and wards levels. Average mortality was higher in small wards and municipal hospitals but the POOR values were 15% and 16% respectively.
  
  
  CONCLUSIONS
  Swedish wards and hospitals in general performed homogeneously well, resulting in a low 30-day mortality rate after HF. In our study, knowledge on a patient's previous hospitalizations was the best predictor of 30-day mortality, and this information did not improve by knowing the sex and country of birth of the patient or where the patient was treated.
authors: Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden.|Research Unit of Chronic Conditions, Bispebjerg University Hospital, Copenhagen, Denmark.
authors: Nermin
authors: N
authors: Ghith
authors: Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden.|Centre for Clinical Research, Västmanland, Uppsala University, Västerås, Sweden.
authors: Philippe
authors: P
authors: Wagner
authors: Research Unit of Chronic Conditions, Bispebjerg University Hospital, Copenhagen, Denmark.
authors: Anne
authors: A
authors: Frølich
authors: Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden.
authors: Juan
authors: J
authors: Merlo
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D018572:Disease-Free Survival; D005260:Female; D006333:Heart Failure / Q000175:diagnosis / Q000453:epidemiology* / Q000628:therapy; D006761:Hospitals; D006801:Humans; D008297:Male; D008875:Middle Aged; D012307:Risk Factors; D012727:Sex Characteristics; D015996:Survival Rate; D013548:Sweden / Q000453:epidemiology