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The Kaiser Permanente inpatient risk adjustment methodology was valid in an external patient population.

Abstract：

OBJECTIVES:Accurately predicting hospital mortality is necessary to measure and compare patient care. External validation of predictive models is required to truly prove their utility. This study assessed the Kaiser Permanente inpatient risk adjustment methodology for hospital mortality in a patient population distinct from that used for its derivation. STUDY DESIGN AND SETTING:Retrospective cohort study at two hospitals in Ottawa, Canada, involving all inpatients admitted between January 1998 and April 2002 (n=188,724). Statistical models for inpatient mortality were derived on a random half of the cohort and validated on the other half. RESULTS:Inpatient mortality was 3.3%. The model using original parameter estimates had excellent discrimination (c-statistic 89.4, 95% confidence interval [CI] 0.891-0.898) but poor calibration. Using data-based parameter estimates, discrimination was excellent (c-statistic 0.915, 95% CI 0.912-0.918) and remained so when patient comorbidity was expressed in the model using the Elixhauser Index (0.901, 0.898-0.904) or the Charlson Index (0.894, 0.891-0.897). These models accurately predicted the risk of hospital death. CONCLUSION:The Kaiser Permanente inpatient risk adjustment methodology is a valid model for predicting hospital mortality risk. It performed equally well regardless of methods used to summarize patient comorbidity.

journal_name

J Clin Epidemiol

journal_title

Journal of clinical epidemiology

authors

van Walraven C,Escobar GJ,Greene JD,Forster AJ

doi

10.1016/j.jclinepi.2009.08.020

subject

Has Abstract

pub_date

2010-07-01 00:00:00

pages

798-803

issue

7

eissn

0895-4356

issn

1878-5921

pii

S0895-4356(09)00273-X

journal_volume

63

pub_type

杂志文章,多中心研究

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