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Identifying Performance Outliers for Stroke Care Based on Composite Score of Process Indicators: an Observational
Chao Wang1, Shaofei Su2, Xi Li1
1Department of Biostatistics, Public Health College, Harbin Medical University , Harbin, China.
Background:
Variability in the quality of stroke care is widespread. Identifying performance-based outlier hospitals based on quality indicators (QIs) has become a common practice.
Objectives:
To develop a tool for identifying performance-based outlier hospitals based on risk-adjusted adherence rates of process indicators.
Design:
Hospitals were classified into five-level outliers based on the observed-to-expected ratio and P value. The composite quality score was derived by summation of the points for each indicator for each hospital, and associations between outlier status and outcomes were determined.
Participants:
Patients diagnosed with acute ischemic stroke, January 1, 2011-May 31, 2017.
Intervention:
N/A MAIN OUTCOME MEASURES: Independence at discharge (the modified Rankin Scale = 0-2).
Key Results:
A total of 501,132 patients from 519 hospitals were identified. From 0.39 to 19.65% of hospitals were identified as high outliers according to various QIs. Composite quality scores ranged from - 20 to 16. Providers that were high outliers based on QI2, QI8, QI9, and QI11 had higher independent rates. For composite quality score, each point increase corresponded to an 8% increase in the odds of independent rate.
Conclusion:
Nationwide variation in the quality of acute stroke care exists at the hospital level. Variability in the quality of stroke care can be captured by our proposed quality score. Applying this quality score as a benchmarking tool could provide audit-level feedback to policymakers and hospitals to aid quality improvement.
