Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/286857 
Year of Publication: 
2021
Citation: 
[Journal:] The European Journal of Health Economics [ISSN:] 1618-7601 [Volume:] 22 [Issue:] 5 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2021 [Pages:] 833-846
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
The goal of this study is to provide empirical evidence of the impact of nurse staffing levels on seven nursing-sensitive patient outcomes (NSPOs) at the hospital unit level. Combining a very large set of claims data from a German health insurer with mandatory quality reports published by every hospital in Germany, our data set comprises approximately 3.2 million hospital stays in more than 900 hospitals over a period of 5 years. Accounting for the grouping structure of our data (i.e., patients grouped in unit types), we estimate cross-sectional, two-level generalized linear mixed models (GLMMs) with inpatient cases at level 1 and units types (e.g., internal medicine, geriatrics) at level 2. Our regressions yield 32 significant results in the expected direction. We find that differentiating between unit types using a multilevel regression approach and including postdischarge NSPOs adds important insights to our understanding of the relationship between nurse staffing levels and NSPOs. Extending our main model by categorizing inpatient cases according to their clinical complexity, we are able to rule out hidden effects beyond the level of unit types.
Subjects: 
Nurse staffing
Nursing-sensitive patient outcomes
Quality of care
Acute care
Multilevel models
JEL: 
J11
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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