Volume 29, Issue 7-8 pp. 778-785
Research Article

Establishing the relationship between nurse staffing and hospital mortality using a clustered discrete-time logistic model

L. Diya

Corresponding Author

L. Diya

Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, Kapucijnenvoer 35, Blok D, Bus 7001, B3000 Leuven, and Universiteit Hasselt, Belgium

Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, Kapucijnenvoer 35, Blok D, Bus 7001, B3000 Leuven, and Universiteit Hasselt, BelgiumSearch for more papers by this author
E. Lesaffre

E. Lesaffre

Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Katholieke Universiteit Leuven, Kapucijnenvoer 35, Blok D, Bus 7001, B3000 Leuven, and Universiteit Hasselt, Belgium

Department of Biostatistics, Erasmus Medical Center, PO Box 2040, 3000 CA Rotterdam, The Netherlands

Search for more papers by this author
K. Van den Heede

K. Van den Heede

Centre for Health Services and Nursing Research, Kapucijnenvoer 35, B-3000 Leuven, Belgium

Search for more papers by this author
W. Sermeus

W. Sermeus

Centre for Health Services and Nursing Research, Kapucijnenvoer 35, B-3000 Leuven, Belgium

Search for more papers by this author
A. Vleugels

A. Vleugels

Centre for Health Services and Nursing Research, Kapucijnenvoer 35, B-3000 Leuven, Belgium

Search for more papers by this author
First published: 08 March 2010
Citations: 7

Abstract

Studies based on aggregated hospital outcome data have established that there is a relationship between nurse staffing and adverse events. However, this result could not be confirmed in Belgium where 96 per cent of the variability of nurse staffing levels over nursing units (belonging to different hospitals) is explained by within-hospital variability. To better appreciate the possible impact of nurse staffing levels on adverse events, we propose a multilevel approach reflecting the complex nature of the data. In particular we suggest a clustered discrete-time logistic model that captures the risks associated with a given unit in the patient's trajectory through the hospital. The model also allows for nurse staffing levels to affect the current and subsequent nursing unit (carry-over effect). In the model ‘time’ is represented by the sequential number of the nursing unit that the patient is passing through. The model incorporates hospital and nursing unit random effects to express that patients treated in the same hospital and taken care of by nurses of the same unit share a common environment. In this study we used Belgian national administrative databases for the year 2003 to assess the relationship between nurse staffing levels and nurse education variables with in-hospital mortality. The analysis was restricted to elective cardiac surgery patients. Lower nursing unit staffing levels in the general nursing units were associated with high in-hospital mortality in units past the traditional cardiac surgery nursing units. Copyright © 2010 John Wiley & Sons, Ltd.

The full text of this article hosted at iucr.org is unavailable due to technical difficulties.