The impact of nurse staffing levels on nursing-sensitive patient outcomes: a multilevel regression approach

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 hosp...

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Veröffentlicht in:The European journal of health economics Jg. 22; H. 5; S. 833 - 846
Hauptverfasser: Dietermann, Karina, Winter, Vera, Schneider, Udo, Schreyögg, Jonas
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin, Heidelberg Springer 01.07.2021
Springer Berlin Heidelberg
Springer Nature B.V
Schlagworte:
Acute care
Aftercare
Clinical outcomes
Cross-Sectional Studies
Economic Policy
Germany
Health Care Management
Health Economics
Humans
Medicine
Medicine & Public Health
Multilevel models
Nurse staffing
Nursing Staff, Hospital
Nursing-sensitive patient outcomes
Original Paper
Patient Discharge
Personnel Staffing and Scheduling
Pharmacoeconomics and Health Outcomes
Public Finance
Public Health
Quality of care
Workforce
Workforce planning
Germany
Nursing-sensitive patient outcomes
J11
Quality of care
Acute care
Nurse staffing
Multilevel models
ISSN:1618-7601, 1618-7598, 1618-7601
Online-Zugang:Volltext
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Zusammenfassung: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.
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ISSN:1618-7601
1618-7598
1618-7601
DOI:10.1007/s10198-021-01292-2