Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhan, Zhe-Wei, Chen, Yu-An, Dong, Yaa-Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7024789/
https://www.ncbi.nlm.nih.gov/pubmed/32103932
http://dx.doi.org/10.2147/COPD.S229646
_version_ 1783498455494164480
author Zhan, Zhe-Wei
Chen, Yu-An
Dong, Yaa-Hui
author_facet Zhan, Zhe-Wei
Chen, Yu-An
Dong, Yaa-Hui
author_sort Zhan, Zhe-Wei
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7024789
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Dove
record_format MEDLINE/PubMed
spelling pubmed-70247892020-02-26 Comparative Performance of Comorbidity Measures in Predicting Health Outcomes in Patients with Chronic Obstructive Pulmonary Disease Zhan, Zhe-Wei Chen, Yu-An Dong, Yaa-Hui Int J Chron Obstruct Pulmon Dis Original Research 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. Dove 2020-02-12 /pmc/articles/PMC7024789/ /pubmed/32103932 http://dx.doi.org/10.2147/COPD.S229646 Text en © 2020 Zhan et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Zhan, Zhe-Wei
Chen, Yu-An
Dong, Yaa-Hui
Comparative Performance of Comorbidity Measures in Predicting Health Outcomes in Patients with Chronic Obstructive Pulmonary Disease
title Comparative Performance of Comorbidity Measures in Predicting Health Outcomes in Patients with Chronic Obstructive Pulmonary Disease
title_full Comparative Performance of Comorbidity Measures in Predicting Health Outcomes in Patients with Chronic Obstructive Pulmonary Disease
title_fullStr Comparative Performance of Comorbidity Measures in Predicting Health Outcomes in Patients with Chronic Obstructive Pulmonary Disease
title_full_unstemmed Comparative Performance of Comorbidity Measures in Predicting Health Outcomes in Patients with Chronic Obstructive Pulmonary Disease
title_short Comparative Performance of Comorbidity Measures in Predicting Health Outcomes in Patients with Chronic Obstructive Pulmonary Disease
title_sort comparative performance of comorbidity measures in predicting health outcomes in patients with chronic obstructive pulmonary disease
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7024789/
https://www.ncbi.nlm.nih.gov/pubmed/32103932
http://dx.doi.org/10.2147/COPD.S229646
work_keys_str_mv AT zhanzhewei comparativeperformanceofcomorbiditymeasuresinpredictinghealthoutcomesinpatientswithchronicobstructivepulmonarydisease
AT chenyuan comparativeperformanceofcomorbiditymeasuresinpredictinghealthoutcomesinpatientswithchronicobstructivepulmonarydisease
AT dongyaahui comparativeperformanceofcomorbiditymeasuresinpredictinghealthoutcomesinpatientswithchronicobstructivepulmonarydisease