Stroke Administrative Severity Index: using administrative data for 30-day poststroke outcomes prediction.

ABSTRACT:

Aim

Current stroke severity scales cannot be used for archival data. We develop and validate a measure of stroke severity at hospital discharge (Stroke Administrative Severity Index [SASI]) for use in billing data.

Methods

We used the NIH Stroke Scale (NIHSS) as the theoretical framework and identified 285 relevant International Classification of Diseases, 9th Revision diagnosis and procedure codes, grouping them into 23 indicator variables using cluster analysis. A 60% sample of stroke patients in Medicare data were used for modeling risk of 30-day postdischarge mortality or discharge to hospice, with validation performed on the remaining 40% and on data with NIHSS scores.

Results

Model fit was good (p > 0.05) and concordance was strong (C-statistic = 0.76-0.83). The

SUBMITTER: Simpson AN 

PROVIDER: S-EPMC6615407 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature