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Activity Number:
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583
- Statistical Methods in Health Services and Performance Profiling
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2018 : 2:00 PM to 3:50 PM
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Sponsor:
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Health Policy Statistics Section
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Abstract #330564
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Presentation
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Title:
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Bayesian Reliability Assessment of Facility-Level Patient Outcome Measures
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Author(s):
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Jianghua He* and Nancy Dunton
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Companies:
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University of Kansas Medical Center and University of Kansas Medical Center
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Keywords:
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Intraclass correlation coefficient;
Emperical Bayesian Statistics;
Quality of patient care
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Abstract:
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Patient health outcome measures at facility-level are often used as quality indicators of patient care. Within-facility variations of such measures often differ among facilities, for which the intra-class correlation coefficient based on equal within-subject variation may not be applicable. Signal-to-noise approach can be used to assess the facility-specific reliability of a measure with different within-subject variation among facilities. Previous studies showed that the reliability score provided by the signal-to-noise approach had a poor correlation with facility ranking based on the outcome measure. In this study, we propose a modified signal-to-noise approach within the Bayesian framework for assessing the reliability of patient outcome measures at facility-level. Simulation studies demonstrated that our approach provides a reliability measure that has a much stronger correlation with facility ranking compared to previous approaches. Our approach is applied to assess the reliability of nursing quality indicators from the National Database of Nursing Quality Indicators.
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Authors who are presenting talks have a * after their name.
