Multi-level models for heart failure patients' 30-day mortality and readmission rates: the relation between patient and hospital factors in administrative data

被引:4
作者
Roshanghalb, Afsaneh [1 ]
Mazzali, Cristina [2 ]
Lettieri, Emanuele [1 ]
机构
[1] Politecn Milan, Dept Management Econ & Ind Engn, Via Lambruschini 4-b, Milan, Italy
[2] Osped Niguarda Ca Granda, Qual & Clin Risk Unit, Piazza Osped Maggiore 3, Milan, Italy
关键词
Quality of care; Hospital care performance; Administrative data; Heart failure; Mortality; Readmission; CARE; PERFORMANCE; OUTCOMES; MANAGEMENT; QUALITY;
D O I
10.1186/s12913-019-4818-2
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: This study aims at gathering evidence about the relation between 30-day mortality and 30-day unplanned readmission and patient and hospital factors. By definition, we refer to 30-day mortality and 30-day unplanned readmission as the number of deaths and non-programmed hospitalizations for any cause within 30 days after the incident heart failure (HF). In particular, the focus is on the role played by hospital-level factors. Methods: A multi-level logistic model that combines patient- and hospital-level covariates has been developed to better disentangle the role played by the two groups of covariates. Later on, hospital outliers in term of better-than-expected/worst-than-expected performers have been identified by comparing expected cases vs. observed cases. Hospitals performance in terms of 30-day mortality and 30-day unplanned readmission rates have been visualized through the creation of funnel plots. Covariates have been selected coherently to past literature. Data comes from the hospital discharge forms for Heart Failure patients in the Lombardy Region (Northern Italy). Considering incident cases for HF in the timespan 2010-2012, 78,907 records for adult patients from 117 hospitals have been collected after quality checks. Results: Our results show that 30-day mortality and 30-day unplanned readmissions are explained by hospital-level covariates, paving the way for the design and implementation of evidence-based improvement strategies. While the percentage of surgical DRG (OR = 1.001; CI (1.000-1.002)) and the hospital type of structure (Research hospitals vs. non-research public hospitals (OR = 0.62; CI (0.48-0.80)) and Non-research private hospitals vs. non-research hospitals OR = 0.75; CI (0.63-0.90)) are significant for mortality, the mean length of stay (OR = 0.96; CI (0.95-0.98)) is significant for unplanned readmission, showing that mortality and readmission rates might be improved through different strategies. Conclusion: Our results confirm that hospital-level covariates do affect quality of care, and that 30-day mortality and 30-day unplanned readmission are affected by different managerial choices. This confirms that hospitals should be accountable for their "added value" to quality of care.
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页数:12
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