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EPI235: Epi Methods in HSR. March 31, 2005 L2 Evaluating Health Services using administrative data 1: Introduction to Risk Adjustment (Dr. Schneeweiss)

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Epi235 epi methods in hsr
EPI235: Epi Methods in HSR

March 31, 2005 L2

Evaluating Health Services using administrative data 1: Introduction to Risk Adjustment (Dr. Schneeweiss)

This lecture gives an overview of the various approaches of adjusting for confounding typical to Health Services Research. The purpose and mechanics of proprietary and non-proprietary risk-adjustment tools for clinical and administrative data, including DRGs, ACGs, and comorbidity indices will be discussed.

Students will explore the value of standard tools for risk adjustment in Health Services studies.

Background reading:

Iezzoni LI: Risk and outcomes. In: Iezzoni LI (ed.): Risk adjustment for measuring healthcare outcomes. Health Administration Press, Chicago, 1997.

Schneeweiss S, Maclure M: Use of Comorbidity Scores for Control of Confounding in Studies using Administrative Databases. Int J Epidemiol 2000,29:891-898.


Remember: A confounder is an independent risk factor that is unbalanced between exposure groups.

(16*920)/(80*184) = 1.0

1.0

2.0

68%

10.0

90%


The Charlson Index: unbalanced between exposure groups.


The Charlson Index for claims data: unbalanced between exposure groups.


The Chronic Disease Score (CDS): unbalanced between exposure groups.


Comorbid conditions according to Elixhauser et al. unbalanced between exposure groups.


CDS revisited: unbalanced between exposure groups.


DRGs: unbalanced between exposure groups.


DRGs: unbalanced between exposure groups.

DRG

159

DRG

161

DRG

160

DRG

162


DRGs: unbalanced between exposure groups.


=> Prediction of future ambulatory care is easier than prediction of health outcomes:

Prior care is a very strong predictor of future care all things equal


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