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Methods Inf Med 1994; 33(02): 196-204
DOI: 10.1055/s-0038-1635006
Original Article
Schattauer GmbH

Comparing Mortality and Morbidity in Hospitals: Theory and Practice of Quality Assessment in Peer Review

R. Brand
1   Department of Medical Statistics, Medical Faculty, Leiden
,
O. J. S. van Hemel
2   Department of Obstetrics and Gynaecology, Reinier de Graaf Hospital, Delft
,
P. M. Elferink-Stinkens
2   Department of Obstetrics and Gynaecology, Reinier de Graaf Hospital, Delft
,
S. P. Verloove-Vanhorick
3   Dutch Institute for Preventive Medicine NIPG, Leiden, The Netherlands
› Author Affiliations
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Publication History

Publication Date:
08 February 2018 (online)

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Abstract:

The incidence of mortality in a specific hospital depends on many risk factors. These risk factors may be divided roughly into two categories. The intake category, consists of those risk factors for which the hospital has hardly any influence upon their incidence; and the care category being those for which the incidence depends partly or completely on the treatment policy of the hospital. A hospital with a high incidence of risk factors in the intake category will have a higher mortality rate than a hospital with a low incidence, even if their care is exactly the same (i. e., if they treat their infants equally well). Therefore, a fair comparison between one hospital and a reference cohort, or among several hospitals (using a national registry) should adjust e. g. correct for those risk factors belonging to the intake category. A practical method is proposed, based on logistic regression, to effectuate such a “fair” judgment. The regression technique enables to compare “observed” and “expected” rates in a specific hospital and to test whether a difference between these rates is statistically significant. Both clinical and statistical aspects of the method are discussed, as well as the actual implementation of an automated annual reporting system. The method has been implemented in the Netherlands as an annual peer review and quality assessment system in obstetric care.

Keywords

Logistic Regression - Comparison - Prediction - Peer Review - Quality Assessment
 

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