A comparison of stroke severity proxy measures for claims data research: A population-based cohort study

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Title:	A comparison of stroke severity proxy measures for claims data research: A population-based cohort study
Authors:	胡雅涵;Sung, Sheng-Feng;Chen, Solomon Chih-Cheng;Hsieh, Cheng-Yang;Li, Chung-Yi;Lai, Edward Chia-Cheng;Hu, Ya-Han
Contributors:	管理學院資訊管理學系
Keywords:	acute ischemic stroke;Aged;Aged, 80 and over;Brain Ischemia - mortality;Brain Ischemia - physiopathology;claims data;Cohort Studies;Confounding Factors (Epidemiology);Databases, Factual - statistics & numerical data;disease severity;Female;Humans;Insurance claims;Intensive Care Units;Logistic Models;Male;Middle Aged;Models, Statistical;outcomes research;pharmacoepidemiology;Risk assessment;Risk Factors;ROC Curve;Severity of Illness Index;Stroke;Stroke - mortality;Stroke - physiopathology;Taiwan;Time Factors
Date:	2016-04-01
Issue Date:	2026-04-23 13:14:01 (UTC+8)
Publisher:	England: Blackwell Publishing Ltd
Abstract:	摘要： Purpose Confounding by disease severity has been viewed as an intractable problem in claims‐based studies. A novel 7‐variable stroke severity index (SSI) was designed for estimating stroke severity by using claims data. This study compared the performance of mortality models with various proxy measures of stroke severity, including the SSI, in patients hospitalized for acute ischemic stroke (AIS). Methods Data from the Taiwan National Health Insurance Research Database (NHIRD) were analyzed. Three proxy measures of stroke severity were evaluated: Measure 1, the SSI; Measure 2, intensive care unit admission and length of stay; and Measure 3, surgical operation, mechanical ventilation, hemiplegia or hemiparesis, and residual neurological deficits. We performed logistic regression by including age, sex, vascular risk factors, Charlson comorbidity index, and one of the proxy measures as covariates to predict 30‐day and 1‐year mortality after AIS. Model discrimination was evaluated using the area under the receiver‐operating characteristic curve (AUC). Results We identified 7551 adult patients with AIS. Models using the SSI (Measure 1) outperformed models using the other proxy measures in predicting 30‐day mortality (AUC 0.892 vs 0.851, p < 0.001 for Measure 2; 0.892 vs 0.853, p < 0.001 for Measure 3) and 1‐year mortality (AUC 0.816 vs 0.784, p < 0.001 for Measure 2; 0.816 vs 0.782, p < 0.001 for Measure 3). Conclusions Using the SSI facilitated risk adjustment for stroke severity in mortality models for patients with AIS. The SSI is a viable methodological tool for stroke outcome studies using the NHIRD. Copyright © 2015 John Wiley & Sons, Ltd. 其他題名： Pharmacoepidemiol Drug Saf 出版者： England: Blackwell Publishing Ltd 出版日期： 2016-04 出處： Pharmacoepidemiology and drug safety, 2016-04, Vol.25 (4), p.438-443 版權： Copyright © 2015 John Wiley & Sons, Ltd. 版權： Copyright © 2016 John Wiley & Sons, Ltd. 識別號： ISSN: 1053-8569 識別號： EISSN: 1099-1557 識別號： DOI: 10.1002/pds.3944 識別號： PMID: 26696591
Appears in Collections:	[Department of Information Management] journal & Dissertation

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