Abstract Details
Activity Number:
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27
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Type:
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Topic Contributed
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Date/Time:
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Sunday, August 4, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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Section for Statistical Programmers and Analysts
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Abstract - #307851 |
Title:
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The Role of Hospital Characteristics in Setting Appropriate Yardsticks for Quality Measurement
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Author(s):
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Frank B Yoon*+ and Alex Bohl and David Jones and Dmitriy Poznyak and Jessica Ross and Eric Schone and Joe Zickafoose and Dejene Ayele
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Companies:
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Mathematica Policy Research and Mathematica Policy Research and Mathematica Policy Research and Mathematica Policy Research and Mathematica Policy Research and Mathematica Policy Research and Mathematica Policy Research and Mathematica Policy Research
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Keywords:
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hierarchical model ;
risk adjustment ;
empirical Bayes ;
hospital profiling
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Abstract:
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Hierarchical models in the AHRQ Quality Indicators (QI) adjust for patient-level risk factors but not for potential variation in quality by hospital attributes, such as teaching status or bed size. This variation is typically modeled by hospital-level random effects, for example, by setting prior means in a Normal distribution that depend on hospital attributes. Alternatively, we evaluate the performance of hierarchical models that assume more flexible random effect distributions than the Normal to better account for underlying variation in quality. Flexible distributions for the random effects might avoid the need to explicitly specify models with hospital attributes while addressing concerns about their use and interpretation in hospital profiling. We will discuss this advantage and demonstrate the application of these enhanced models in a nationally representative inpatient claims database.
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Authors who are presenting talks have a * after their name.
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