Are Patient Safety Indicators Related to Widely Used Measures of Hospital Quality?
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Patient safety indicators (PSIs) are screening tools that use administrative data to identify potential complications of care and are being increasingly used as measures of hospital safety. It is unknown whether PSIs are related to standard quality metrics.
To examine the relationship between select PSIs and measures of hospital quality.
Design, Setting, and Participants
We used the 2003 MedPAR dataset to examine the performance of 4,504 acute-care hospitals on four medical PSIs among Medicare enrollees.
Main Outcome Measures
We used bivariate and multivariate techniques to examine the relationship between PSI performance and quality scores from the Hospital Quality Alliance program, risk-adjusted mortality rates, and selection as a top hospital by US News & World Report.
We found inconsistent and usually poor associations among the PSIs and other hospital quality measures with the exception of “failure to rescue,” which was consistently associated with better performance on all quality measures tested. For example, hospitals in the top quartile of failure to rescue performance had a 0.9% better summary performance score in acute myocardial infarction (AMI) processes and a 22% lower mortality rate in AMI compared to hospitals in the bottom quartile of failure to rescue (p < 0.01 for both comparisons). Death in low mortality DRG, decubitus ulcer, and infection due to medical care generally had poor or often inverse relationships with the other quality measures.
With the exception of failure to rescue, we found poor or inverse relationships between PSIs and other measures of healthcare quality. Whether the lack of relationship is due to the limitations of the PSIs is unknown, but suggests that PSIs need further validation before they are employed broadly.
KEY WORDSpatient safety indicators (PSIs) hospital quality scores unsafe medical care
We are grateful to E. John Orav, PhD, for his statistical input, Jeffery Geppert, JD, for his help with the PSI software and Drs. Saul Weingart and Lisa Iezzoni for their insightful comments on earlier versions of the manuscript.
This material is the result of work supported with resources and the use of facilities at the Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System.
Conflict of Interest
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