Abstract Details
Activity Number:
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504
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Type:
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Contributed
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Date/Time:
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Wednesday, August 6, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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Health Policy Statistics Section
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Abstract #313050
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View Presentation
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Title:
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A Comparison of Cross-Sectional and Longitudinal Analyses for Adverse Events Data
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Author(s):
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Douglas Morrison*+ and Manisha Desai and Catherine Curtin and Tina Hernandez-Boussard
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Companies:
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Stanford University and Stanford University and Stanford University and Stanford University
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Keywords:
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health care quality ;
hospital quality measures ;
administrative data ;
longitudinal analysis ;
difference score ;
quality indicators
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Abstract:
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Background: Previous studies of inpatient adverse events used cross-sectional data to associate hospital characteristics such as nurse-to-patient ratio (NPR) with outcomes such as failure to rescue from complications (FTR). These studies are vulnerable to confounding. We sought to compare such an analysis with a longitudinal analysis that associates changes in NPR with changes in FTR. Data: We took NPRs from the AHA surveys and FTR rates from the California HCUP SID data. Methods: For the cross-sectional model, we treated each year:hospital combination as a separate data point and regressed FTR on NPR. For the longitudinal model, we regressed the 2008-2011 change in FTR on the change in NPR. Results: The cross-sectional model found a significant association between NPR and FTR (est. corr. -11%, p < 0.01). The longitudinal model found no association (est. corr. -0.6%, p = 0.91). Conclusions: The longitudinal and cross-sectional analyses contradict each other; the longitudinal analysis seems less vulnerable to confounding. By pairing each hospital with its previous performance, we limit possible confounders to those that also change in the same time interval.
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Authors who are presenting talks have a * after their name.
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