Abstract
BackgroundThis 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.MethodsA 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.ResultsOur 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.ConclusionOur 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.
Highlights
This study aims at gathering evidence about the relation between 30-day mortality and 30-day unplanned readmission and patient and hospital factors
As indicators of hospital quality of care, we considered the well-established measures of quality of treatment on short-term outcomes for Heart Failure (HF) patients [13, 14]: 30-day mortality and 30-day unplanned readmission
Measurement of quality of care In this study, we refer to 30-day mortality as the number of deaths for any cause within 30 days after the incident HF admission and 30-day unplanned readmission as the number of non-programmed hospitalizations for any cause within 30 days after the incident HF admission
Summary
This study aims at gathering evidence about the relation between 30-day mortality and 30-day unplanned readmission and patient and hospital factors. Recent studies–for a review refer to Lega et al (2013) [6]–claim that management practices affect hospital quality of care Grounding on this emerging evidence, Lega et al (2013) [6] argued that “empirical efforts of researchers must extend our understanding of the relationship between management practices and performance” Past studies that investigated the relationship between management practices and quality of care proved it through either self-reported surveys or expert opinion In this view, regulators and hospital managers pointed out that current evidence about the existence of this relationship is not enough robust as studies on hospital performance based on administrative data [7,8,9]–even if limited to patient-related covariates. While the mainstream approach is to analyze them as a single outcome [4], an increasing number of scholars [2, 12] analyzed them separately to better understand what explains different quality of care and the role played by different managerial alternatives [13]
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