To evaluate whether routine laboratory data can improve the ability to compare risk-adjusted outcomes of different medical wards, and to detect'outlier'wards with significantly better or worse outcome.
Patient data were taken from the Combined Patient Database Systematic Management and Research Tool, a database created by merging different computerized sources at a tertiary care hospital.
All patients admitted to internal wards with the diagnosis of pneumonia during the years 1991-1995 were included (n=2734).
The outcome variable was mortality 30 days post-admission.
We used three comorbidity measures based on ICD-9-CM codes as possible predictors of mortality :
secondary diagnoses ;
the Health Care Financing Administration severity index ;
and the Charlson comorbidity index.
Models were created using logistic regression.
To each model, laboratory data gathered in the first 48 hours after admission were added.
To identify'outlier'services we determined whether the patients'ward was an independent predictor of mortality.
The area under the receiver operator curve (ROC) of the models was used for comparisons.
The area under the ROC was 0.65-0.72 for the models based on age and comorbid diagnoses.
The addition of laboratory data improved markedly the discriminatory ability of each of the models, as reflected by an increase in the area under the ROC to 0.83-0.84. (...)
Mots-clés Pascal : Pneumonie, Bactériose, Infection, Maladie, Modèle, Epidémiologie, Méthode étude, Exploration, Médecin, Pratique professionnelle, Hôpital, Secteur public, Economie, Sang, Examen laboratoire, Economie santé
Mots-clés Pascal anglais : Pneumonia, Bacteriosis, Infection, Disease, Models, Epidemiology, Investigation method, Exploration, Physician, Professional practice, Hospital, Public sector, Economy, Blood, Laboratory investigations, Health economy
Notice produite par :
ORS Auvergne - Observatoire Régional de la Santé d'Auvergne
Code Inist : 002B30A11. Création : 11/09/1998.