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Abstract Details
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Activity Number:
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75
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Type:
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Contributed
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Date/Time:
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Sunday, July 31, 2011 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Health Policy Statistics
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| Abstract - #301567 |
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Title:
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On the Accuracy of Classifying Hospitals Using Performance Measures
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Author(s):
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Yulei He*+ and Sharon-Lise Theresa Normand
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Companies:
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Harvard Medical School and Harvard Medical School
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Address:
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, , MA, 02115, U.S.A.
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Keywords:
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area under the curve ;
hospital profiling ;
nonnormality ;
random-effects model ;
sensitivity ;
pay for performance
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Abstract:
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Provider performance data are rapidly available as they can provide valuable information about the associated quality of care. Statistical methods have been developed for evaluating the quality of providers. Oftentimes, practical interest lie in classifying hospitals into ties based on the estimates of their quality. However, the accuracy of the classification methods is less clear. We assess the accuracy of classification approaches using both theoretical derivation and Monte Carlo simulation. The results can assist us in the design of hospital profiling studies. This work is motivated from the U.S Medicare's national Hospital Compare database, which is available to public and includes multiple process measures for patients treated for certain diseases.
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