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Identification of cancer patients using claims data from health insurance systems: A real-world comparative study
OBJECTIVE: To evaluate the accuracy of identifying cancer patients by use of medical claims data in a health insurance system in China, and provide the basis for establishing the claims-based cancer surveillance system in China. METHODS: We chose Hua County, Henan Province as the study site, and ran...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6736657/ https://www.ncbi.nlm.nih.gov/pubmed/31564812 http://dx.doi.org/10.21147/j.issn.1000-9604.2019.04.13 |
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author | Tian, Hongrui Xu, Ruiping Li, Fenglei Guo, Chuanhai Zhang, Lixin Liu, Zhen Liu, Mengfei Pan, Yaqi He, Zhonghu Ke, Yang |
author_facet | Tian, Hongrui Xu, Ruiping Li, Fenglei Guo, Chuanhai Zhang, Lixin Liu, Zhen Liu, Mengfei Pan, Yaqi He, Zhonghu Ke, Yang |
author_sort | Tian, Hongrui |
collection | PubMed |
description | OBJECTIVE: To evaluate the accuracy of identifying cancer patients by use of medical claims data in a health insurance system in China, and provide the basis for establishing the claims-based cancer surveillance system in China. METHODS: We chose Hua County, Henan Province as the study site, and randomly selected 300 and 1,200 qualified inpatient electronic medical records (EMRs) as well as the New Rural Cooperative Medical Scheme (NCMS) claims records for cancer patients in Hua County People’s Hospital (HCPH) and Anyang Cancer Hospital (ACH) in 2017. Diagnostic information for NCMS claims was evaluated on an individual level, and sensitivity and positive predictive value (PPV) were calculated taking the EMRs as the gold standard. RESULTS: The sensitivity of NCMS was 95.2% (93.8%−96.3%) and 92.0% (88.3%−94.8%) in ACH and HCPH, respectively. The PPV of the NCMS was 97.8% (96.7%−98.5%) in ACH and 89.0% (84.9%−92.3%) in HCPH. Overall, the weighted and combined sensitivity and PPV of NCMS in Hua County was 93.1% and 92.1%, respectively. Significantly higher sensitivity and PPV in identifying patients with common cancers than non-common cancers were detected in HCPH and ACH separately (P<0.01). CONCLUSIONS: Identification of cancer patients by use of the NCMS is accurate on individual level, and it is therefore feasible to conduct claims-based cancer surveillance in areas not covered by cancer registries in China. |
format | Online Article Text |
id | pubmed-6736657 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-67366572019-09-27 Identification of cancer patients using claims data from health insurance systems: A real-world comparative study Tian, Hongrui Xu, Ruiping Li, Fenglei Guo, Chuanhai Zhang, Lixin Liu, Zhen Liu, Mengfei Pan, Yaqi He, Zhonghu Ke, Yang Chin J Cancer Res Original Article OBJECTIVE: To evaluate the accuracy of identifying cancer patients by use of medical claims data in a health insurance system in China, and provide the basis for establishing the claims-based cancer surveillance system in China. METHODS: We chose Hua County, Henan Province as the study site, and randomly selected 300 and 1,200 qualified inpatient electronic medical records (EMRs) as well as the New Rural Cooperative Medical Scheme (NCMS) claims records for cancer patients in Hua County People’s Hospital (HCPH) and Anyang Cancer Hospital (ACH) in 2017. Diagnostic information for NCMS claims was evaluated on an individual level, and sensitivity and positive predictive value (PPV) were calculated taking the EMRs as the gold standard. RESULTS: The sensitivity of NCMS was 95.2% (93.8%−96.3%) and 92.0% (88.3%−94.8%) in ACH and HCPH, respectively. The PPV of the NCMS was 97.8% (96.7%−98.5%) in ACH and 89.0% (84.9%−92.3%) in HCPH. Overall, the weighted and combined sensitivity and PPV of NCMS in Hua County was 93.1% and 92.1%, respectively. Significantly higher sensitivity and PPV in identifying patients with common cancers than non-common cancers were detected in HCPH and ACH separately (P<0.01). CONCLUSIONS: Identification of cancer patients by use of the NCMS is accurate on individual level, and it is therefore feasible to conduct claims-based cancer surveillance in areas not covered by cancer registries in China. AME Publishing Company 2019-08 /pmc/articles/PMC6736657/ /pubmed/31564812 http://dx.doi.org/10.21147/j.issn.1000-9604.2019.04.13 Text en Copyright © 2019 Chinese Journal of Cancer Research. All rights reserved. http://creativecommons.org/licenses/by-nc-sa/4.0/ This work is licensed under a Creative Commons Attribution-Non Commercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/ |
spellingShingle | Original Article Tian, Hongrui Xu, Ruiping Li, Fenglei Guo, Chuanhai Zhang, Lixin Liu, Zhen Liu, Mengfei Pan, Yaqi He, Zhonghu Ke, Yang Identification of cancer patients using claims data from health insurance systems: A real-world comparative study |
title | Identification of cancer patients using claims data from health insurance systems: A real-world comparative study |
title_full | Identification of cancer patients using claims data from health insurance systems: A real-world comparative study |
title_fullStr | Identification of cancer patients using claims data from health insurance systems: A real-world comparative study |
title_full_unstemmed | Identification of cancer patients using claims data from health insurance systems: A real-world comparative study |
title_short | Identification of cancer patients using claims data from health insurance systems: A real-world comparative study |
title_sort | identification of cancer patients using claims data from health insurance systems: a real-world comparative study |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6736657/ https://www.ncbi.nlm.nih.gov/pubmed/31564812 http://dx.doi.org/10.21147/j.issn.1000-9604.2019.04.13 |
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