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BMC Health Serv Res. 2016 Sep 22;16(1):509.

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

Author information

1
Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chiayi Christian Hospital, 539 Zhongxiao Road, East District, Chiayi City, 60002, Taiwan.
2
Department of Neurology, Tainan Sin Lau Hospital, 57, Section 1, Dongmen Road, East District, Tainan, 70142, Taiwan.
3
Department of Neurology, Chi Mei Medical Center, 901 Zhonghua Road, Yongkang District, Tainan, 710, Taiwan.
4
Department of Neurology, Landseed Hospital, 77 Guangtai Road, Pingjhen District, Taoyuan, Taiwan.
5
Department of Neurology, National Taiwan University Hospital, 7 Zhongshan South Road, Zhongzheng District, Taipei, 10002, Taiwan.
6
Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, 1 University Road, East District, Tainan, 701, Taiwan.
7
School of Pharmacy, Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, 1 University Road, East District, Tainan, 701, Taiwan.
8
Department of Information Management and Institute of Healthcare Information Management, National Chung Cheng University, 168 University Road, Min-Hsiung, Chiayi County, 62102, Taiwan. yahan.hu@mis.ccu.edu.tw.

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.

KEYWORDS:

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

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