Determinants of between‐hospital variations in outcomes for patients admitted with COPD exacerbations: findings from a nationwide clinical audit (AUDIPOC) in Spain. Issue 9 (4th February 2015)

• Record Type: Journal Article
• Authors: Pozo‐Rodríguez, F.; Castro‐Acosta, A.; Alvarez, C. J.; López‐Campos, J. L.; Forte, A.; López‐Quilez, A.; Agustí, A.; Abraira, V.; the AUDIPOC Study Group
• Is Part Of: International journal of clinical practice. Volume 69:Issue 9(2015)
• Page Start: 938
• Page End: 947
• Publication Date: 2015-02-04
• Subjects: Clinical medicine -- Periodicals; Medicine -- Periodicals; 610.5
• DOI: 10.1111/ijcp.12601
• Languages: English
• ISSNs: 1368-5031

Abstract

<abstract abstract-type="main" id="ijcp12601-abs-0001"> <title>Summary</title> <sec id="ijcp12601-sec-0001" sec-type="section"> <title>Background</title> <p>Previous studies have demonstrated significant variability in the processes of care and outcomes of chronic obstructive pulmonary disease (COPD) exacerbations. The AUDIPOC is a Spanish nationwide clinical audit that identified large between‐hospital variations in care and clinical outcomes. Here, we test the hypothesis that these variations can be attributed to either patient characteristics, hospital characteristics and/or the so‐called hospital‐clustering effect, which indicates that patients with similar characteristics may experience different processes of care and outcomes depending on the hospital to which they are admitted.</p> </sec> <sec id="ijcp12601-sec-0002" sec-type="section"> <title>Methods</title> <p>A clinical audit of 5178 COPD patients consecutively admitted to 129 Spanish public hospitals was performed, with a 90‐day follow‐up. Multilevel regression analysis was conducted to model the probability of patients experiencing adverse outcomes. For each outcome, an <italic>empty</italic> model (with no independent variables) was fitted to assess the clustering effect, followed by a model <italic>adjusted</italic> for the patient‐ and hospital‐level covariables. The hospital‐clustering effect was estimated using the intracluster correlation coefficient (ICC); the cluster heterogeneity was estimated with the median odds ratio (MOR), and the coefficients of predictors were estimated with the odds ratio (OR).</p> </sec> <sec id="ijcp12601-sec-0003" sec-type="section"> <title>Results</title> <p>In the <italic>empty</italic> models, the ICC (MOR) for inpatient mortality and the follow‐up mortality and readmission were 0.10 (1.80), 0.08 (1.65) and 0.01 (1.24), respectively. In the <italic>adjusted</italic> models, the variables that most represented the patients' clinical conditions and interventions were identified as outcome predictors and further reduced the hospital variations. By contrast, the resource factors were primarily unrelated with outcomes.</p> </sec> <sec id="ijcp12601-sec-0004" sec-type="section"> <title>Conclusions</title> <p>This study demonstrates a noteworthy reduction in the observed crude between‐hospital variation in outcomes after accounting for the hospital‐cluster effect and the variables representing patient's clinical conditions. This emphasises the predictor importance of the patients' clinical conditions and interventions, and understates the impacts of hospital resources and organisational factors.</p> </sec> </abstract>