AHA Journals, Author Interviews, Health Care Systems, Outcomes & Safety, Stroke / 29.10.2015
NIHSS Stroke Database is Incomplete and May Have Selection Bias
MedicalResearch.com Interview with:
Mathew J. Reeves BVSc, PhD, FAHA
Professor, Department of Epidemiology and Biostatistics,
Michigan State University
East Lansing, MI 48824
Medical Research: What is the background for this study?
Dr. Reeves: The National Institutes of Health Stroke Scale (NIHSS) is the single most important prognostic factor in predicting outcomes of individual stroke patients. NIHSS data is obviously important at the patient level but also at a hospital level since the case mix of stroke patients are assumed to vary widely across different hospitals and referral centers.
Measuring stroke outcomes at a hospital level is becoming increasingly important as work proceeds in the US to develop integrated stroke systems of care. But it is also very relevant to the new payment models being introduced by CMS which are based on hospital rankings that are developed from statistical risk adjustment models. One would expect that NIHSS would be a major contributor to these models but currently a major limitation is that NIHSS is incompletely documented in clinical registries such as GWTG-Stroke, and is completely absent from administrative data.
The problem of missing NIHSS data plays havoc with the ability to risk adjust stroke outcomes across hospitals. Missing data results is a smaller number of stroke cases being included in the risk adjusted calculations for a given hospital which results in greater uncertainty over what the actual hospital outcomes are. Further there is concern that NIHSS data is not missing at random, and so the NIHSS data that is documented may represent a biased selection of all the cases that a hospital admits. This too could have important consequences for hospital rankings.
To determine the degree of potential bias in the documentation of NIHSS data this study examined trends in and predictors of documentation of NIHSS across 10 years of data (2003-2012) in the GWTG-Stroke program.
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