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008			220622b xxu||||| |||| 00| 0 eng d
040			_cH12O
041			_aeng
100			_9702 _aPozo Rodríguez, Francisco _eNeumología _eInstituto de Investigación i+12 (2013-)
100			_92606 _aCastro Acosta, Ady _eInstituto de Investigación i+12
100			_91198 _aÁlvarez González, C. J. _eNeumología
245	0	0	_aDeterminants of between-hospital variations in outcomes for patients admitted with COPD exacerbations: findings from a nationwide clinical audit (AUDIPOC) in Spain. _h[artículo]
260			_bInternational journal of clinical practice, _c2015
300			_a69(9):938-47.
500			_aFormato Vancouver: Pozo Rodríguez F, Castro Acosta A, Alvarez CJ, López Campos JL, Forte A, López Quilez Aet al; AUDIPOC Study Group. Determinants of between-hospital variations in outcomes for patients admitted with COPD exacerbations: findings from a nationwide clinical audit (AUDIPOC) in Spain. Int J Clin Pract. 2015 Sep;69(9):938-47.
501			_aPMID: 25651319 PMC5024082
504			_aContiene 41 referencias
520			_aBackground: 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. Methods: 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 empty model (with no independent variables) was fitted to assess the clustering effect, followed by a model adjusted 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). Results: In the empty 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 adjusted 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. Conclusions: 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.
710			_988 _aServicio de Neumología
710			_9625 _aInstituto de Investigación imas12
856			_uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5024082/ _yAcceso libre
942			_2ddc _cART _n0