Validation of a novel claims-based stroke severity index in patients with intracerebral hemorrhage

Ling Chien Hung, Sheng Feng Sung, Cheng Yang Hsieh, Ya Han Hu, Huey Juan Lin, Yu Wei Chen, Yea Huei Kao Yang, Sue Jane Lin

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

Background: Stroke severity is an important outcome predictor for intracerebral hemorrhage (ICH) but is typically unavailable in administrative claims data. We validated a claims-based stroke severity index (SSI) in patients with ICH in Taiwan. Methods: Consecutive ICH patients from hospital-based stroke registries were linked with a nationwide claims database. Stroke severity, assessed using the National Institutes of Health Stroke Scale (NIHSS), and functional outcomes, assessed using the modified Rankin Scale (mRS), were obtained from the registries. The SSI was calculated based on billing codes in each patient's claims. We assessed two types of criterion-related validity (concurrent validity and predictive validity) by correlating the SSI with the NIHSS and the mRS. Logistic regression models with or without stroke severity as a continuous covariate were fitted to predict mortality at 3, 6, and 12 months. Results: The concurrent validity of the SSI was established by its significant correlation with the admission NIHSS (r = 0.731; 95% confidence interval [CI], 0.705-0.755), and the predictive validity was verified by its significant correlations with the 3-month (r = 0.696; 95% CI, 0.665-0.724), 6-month (r = 0.685; 95% CI, 0.653-0.715) and 1-year (r = 0.664; 95% CI, 0.622-0.702) mRS. Mortality models with NIHSS had the highest area under the receiver operating characteristic curve, followed by models with SSI and models without any marker of stroke severity. Conclusions: The SSI appears to be a valid proxy for the NIHSS and an effective adjustment for stroke severity in studies of ICH outcome with administrative claims data.

Original languageEnglish
Pages (from-to)24-29
Number of pages6
JournalJournal of epidemiology
Volume27
Issue number1
DOIs
Publication statusPublished - 2017

All Science Journal Classification (ASJC) codes

  • Epidemiology

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