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ISSN: 2333-9721
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-  2019 

Tips for calculating and displaying risk

DOI: 10.1177/1536867X19854021

Keywords: st0562,risk adjustment,bootstrap,caterpillar plot,eclplot,funnel plot,generalized estimating equations,healthcare quality assessment,hospital profiling,mfpboot,mfpboot bif,multivariable modeling,outcomes research,qic,riskstandardized mortality rates,stability,xtgee

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Abstract:

A major challenge of outcomes research is measuring hospital performance using readily available administrative data. When the outcome measure is mortality or morbidity, rates are adjusted to account for preexisting conditions that may confound their assessment. However, the concept of “risk-adjusted” outcomes is frequently misunderstood. In this article, we try to clarify things, and we describe Stata tools for appropriately calculating and displaying risk-standardized outcome measures. We offer practical guidance and illustrate the application of these tools to an example based on real data (30-day mortality following acute myocardial infarction in Latvia)

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