• Mathew J Reeves, Julia Gargano, Kimberly S Maier, Joseph P Broderick, Michael Frankel, Kenneth A LaBresh, Charles J Moomaw, and Lee Schwamm.
• Department of Epidemiology, Michigan State University, East Lansing, MI 48824, USA. reevesm@msu.edu
• Stroke. 2010 Dec 1; 41 (12): 2924-31.

Background And PurposeQuality of care may be influenced by patient and hospital factors. Our goal was to use multilevel modeling to identify patient-level and hospital-level determinants of the quality of acute stroke care in a stroke registry.MethodsDuring 2001 to 2002, data were collected for 4897 ischemic stroke and TIA admissions at 96 hospitals from 4 prototypes of the Paul Coverdell National Acute Stroke Registry. Duration of data collection varied between prototypes (range, 2-6 months). Compliance with 8 performance measures (recombinant tissue plasminogen activator treatment, antithrombotics < 24 hours, deep venous thrombosis prophylaxis, lipid testing, dysphagia screening, discharge antithrombotics, discharge anticoagulants, smoking cessation) was summarized in a composite opportunity score defined as the proportion of all needed care given. Multilevel linear regression analyses with hospital specified as a random effect were conducted.ResultsThe average hospital composite score was 0.627. Hospitals accounted for a significant amount of variability (intraclass correlation = 0.18). Bed size was the only significant hospital-level variable; the mean composite score was 11% lower in small hospitals (≤ 145 beds) compared with large hospitals (≥ 500 beds). Significant patient-level variables included age, race, ambulatory status documentation, and neurologist involvement. However, these factors explained < 2.0% of the variability in care at the patient level.ConclusionsMultilevel modeling of registry data can help identify the relative importance of hospital-level and patient-level factors. Hospital-level factors accounted for 18% of total variation in the quality of care. Although the majority of variability in care occurred at the patient level, the model was able to explain only a small proportion.

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