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Comparative Performance of Comorbidity Measures in Predicting Health Outcomes in Patients with Chronic Obstructive Pulmonary Disease

Authors Zhan ZW, Chen YA, Dong YH

Received 3 September 2019

Accepted for publication 16 January 2020

Published 12 February 2020 Volume 2020:15 Pages 335—344

DOI https://doi.org/10.2147/COPD.S229646

Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 2

Editor who approved publication: Prof. Dr. Chunxue Bai


Zhe-Wei Zhan,1 Yu-An Chen,1,2 Yaa-Hui Dong1,2

1Faculty of Pharmacy, School of Pharmaceutical Science, National Yang-Ming University, Taipei 112, Taiwan; 2Institute of Public Health, School of Medicine, National Yang-Ming University, Taipei 112, Taiwan

Correspondence: Yaa-Hui Dong
Faculty of Pharmacy, School of Pharmaceutical Science, National Yang-Ming University, 155, Sec.2, Linong Street, Taipei 112, Taiwan
Tel +886 2-28267986
Fax +886 2-28237829
Email yaahuidong@gmail.com

Purpose: Multiple studies have suggested that comorbidities pose negative impacts on the survival of patients with chronic obstructive pulmonary disease (COPD); few have applied comorbidity measures driven from health insurance claims databases to predict various health outcomes. We aimed to examine the performance of commonly used comorbidity measures based on diagnosis and pharmacy dispensing claims information in predicting future death and hospitalization in COPD patients.
Methods: We identified COPD patients in a population-based Taiwanese database. We built logistic regression models with age, sex, and baseline comorbidities measured by either diagnosis or pharmacy claims information as predictors of subsequent-year death or hospitalization in a random 50% sample and validated the discrimination in the other 50%. The diagnosis-based comorbidity measures included the Charlson Index and the Elixhauser comorbidity measure; the pharmacy-based comorbidity measures included the updated Chronic Disease Score (CDS) and the Pharmacy-Based Comorbidity Index (PBDI).
Results: We identified 428,251 eligible patients. For overall death, the Elixhauser comorbidity measure showed the best predictive performance (c-statistic=0.832), followed by the PBDI (c-statistic=0.822), the Charlson Index (c-statistic=0.815), and the updated CDS (c-statistic=0.808). For overall hospitalization, the PBDI (c-statistics=0.730) and the Elixhauser comorbidity measure (c-statistics=0.724) outperformed the updated CDS (c-statistics=0.714) and the Charlson Index (c-statistics=0.710). For hospitalization due to cardiovascular, cerebrovascular, or respiratory diseases, the comorbidity models showed similar predictive ranks and demonstrated c-statistics higher than 0.75. However, none of the models could adequately predict hospitalization due to other reasons (c-statistics < 0.60).
Conclusion: Our study comprehensively compared the predictive performance of comorbidity measures. The Elixhauser comorbidity measure and the PBDI are useful tools for describing comorbid conditions and predicting health outcomes in COPD patients.

Keywords: chronic obstructive pulmonary disease, diagnosis-based comorbidity measures, pharmacy-based comorbidity measures, health outcomes, health insurance claims database

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