Validity of a stroke severity index for administrative claims data research: a retrospective cohort study

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

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

Background: Ascertaining stroke severity in claims data-based studies is difficult because clinical information is unavailable. We assessed the predictive validity of a claims-based stroke severity index (SSI) and determined whether it improves case-mix adjustment. Methods: We analyzed patients with acute ischemic stroke (AIS) from hospital-based stroke registries linked with a nationwide claims database. We estimated the SSI according to patient claims data. Actual stroke severity measured with the National Institutes of Health Stroke Scale (NIHSS) and functional outcomes measured with the modified Rankin Scale (mRS) were retrieved from stroke registries. Predictive validity was tested by correlating SSI with mRS. Logistic regression models were used to predict mortality. Results: The SSI correlated with mRS at 3 months (Spearman rho = 0.578; 95 % confidence interval [CI], 0.556-0.600), 6 months (rho = 0.551; 95 % CI, 0.528-0.574), and 1 year (rho = 0.532; 95 % CI 0.504-0.560). Mortality models with the SSI demonstrated superior discrimination to those without. The AUCs of models including the SSI and models with the NIHSS did not differ significantly. Conclusions: The SSI correlated with functional outcomes after AIS and improved the case-mix adjustment of mortality models. It can act as a valid proxy for stroke severity in claims data-based studies.

Original languageEnglish
Article number509
Pages (from-to)1-9
Number of pages9
JournalBMC Health Services Research
Volume16
Issue number1
DOIs
StatePublished - 22 Sep 2016

Keywords

  • Acute ischemic stroke
  • Claims data
  • Disease severity
  • National Health Insurance Research Database
  • Outcomes research

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