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Validation of coding algorithms for identifying people with viral hepatitis using claims data according to different standard references

BACKGROUND: To assess the performance of various coding algorithms for identifying people with hepatitis B virus (HBV) and hepatitis C virus (HCV) using claims data according to different reference standards (RSs) and study periods (SPs). METHODS: A proportional random sampling of 10,000 patients ag...

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Autores principales: Sheu, Ming-Jen, Chin, Tsung-Wei, Ku, Fang-Ping, Li, Chung-Yi, Li, Sheng-Tun, Lu, Tsung-Hsueh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8897839/
https://www.ncbi.nlm.nih.gov/pubmed/35246067
http://dx.doi.org/10.1186/s12879-022-07212-w
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author Sheu, Ming-Jen
Chin, Tsung-Wei
Ku, Fang-Ping
Li, Chung-Yi
Li, Sheng-Tun
Lu, Tsung-Hsueh
author_facet Sheu, Ming-Jen
Chin, Tsung-Wei
Ku, Fang-Ping
Li, Chung-Yi
Li, Sheng-Tun
Lu, Tsung-Hsueh
author_sort Sheu, Ming-Jen
collection PubMed
description BACKGROUND: To assess the performance of various coding algorithms for identifying people with hepatitis B virus (HBV) and hepatitis C virus (HCV) using claims data according to different reference standards (RSs) and study periods (SPs). METHODS: A proportional random sampling of 10,000 patients aged ≥ 20 years in a health care system in Southern Taiwan were enrolled as study participants. We used three hierarchical RSs (RS1: having positive results of laboratory tests; R2: having RS1 or having prescriptions of anti-HBV or anti-HCV medications; R3: having R1 or R2 or having textual diagnosis recorded in electrical medical records) with three SPs (4-, 8-, and 12-years) to calculate positive predictive value (PPV) and sensitivity (Sen) of 6 coding algorithms using HBV- and HCV-related International Classification of Disease Tenth Revision Clinical Modification (ICD-10-CM) codes in Taiwan National Health Insurance claims data for years 2016–2019. RESULTS: Of 10,000 enrolled participants, the number of participants had confirmed HBV and HCV was 146 and 165, respectively according to RS1 with 4-years SP and increased to 729 and 525, respectively according to RS3 with 12-years SP. For both HBV and HCV, the PPV was lowest according to RS1 and highest according to RS3. The longer the SP, the higher the PPV. However, the Sen was highest according to RS2 with 4-years SP. For both HBV and HCV, the coding algorithm with highest PPV and Sen was “ ≥ 3 outpatient codes” and “ ≥ 2 outpatient or ≥ 1 inpatients codes,” respectively. CONCLUSIONS: In conclusion, using different RSs with different SPs would result in different estimation of PPV and Sen. To achieve the best yield of both PPV and Sen, the optimal coding algorithm is “ ≥ 2 outpatients or ≥ 1 inpatients codes” for identifying people with HBV or HCV. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07212-w.
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spelling pubmed-88978392022-03-14 Validation of coding algorithms for identifying people with viral hepatitis using claims data according to different standard references Sheu, Ming-Jen Chin, Tsung-Wei Ku, Fang-Ping Li, Chung-Yi Li, Sheng-Tun Lu, Tsung-Hsueh BMC Infect Dis Research BACKGROUND: To assess the performance of various coding algorithms for identifying people with hepatitis B virus (HBV) and hepatitis C virus (HCV) using claims data according to different reference standards (RSs) and study periods (SPs). METHODS: A proportional random sampling of 10,000 patients aged ≥ 20 years in a health care system in Southern Taiwan were enrolled as study participants. We used three hierarchical RSs (RS1: having positive results of laboratory tests; R2: having RS1 or having prescriptions of anti-HBV or anti-HCV medications; R3: having R1 or R2 or having textual diagnosis recorded in electrical medical records) with three SPs (4-, 8-, and 12-years) to calculate positive predictive value (PPV) and sensitivity (Sen) of 6 coding algorithms using HBV- and HCV-related International Classification of Disease Tenth Revision Clinical Modification (ICD-10-CM) codes in Taiwan National Health Insurance claims data for years 2016–2019. RESULTS: Of 10,000 enrolled participants, the number of participants had confirmed HBV and HCV was 146 and 165, respectively according to RS1 with 4-years SP and increased to 729 and 525, respectively according to RS3 with 12-years SP. For both HBV and HCV, the PPV was lowest according to RS1 and highest according to RS3. The longer the SP, the higher the PPV. However, the Sen was highest according to RS2 with 4-years SP. For both HBV and HCV, the coding algorithm with highest PPV and Sen was “ ≥ 3 outpatient codes” and “ ≥ 2 outpatient or ≥ 1 inpatients codes,” respectively. CONCLUSIONS: In conclusion, using different RSs with different SPs would result in different estimation of PPV and Sen. To achieve the best yield of both PPV and Sen, the optimal coding algorithm is “ ≥ 2 outpatients or ≥ 1 inpatients codes” for identifying people with HBV or HCV. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07212-w. BioMed Central 2022-03-04 /pmc/articles/PMC8897839/ /pubmed/35246067 http://dx.doi.org/10.1186/s12879-022-07212-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Sheu, Ming-Jen
Chin, Tsung-Wei
Ku, Fang-Ping
Li, Chung-Yi
Li, Sheng-Tun
Lu, Tsung-Hsueh
Validation of coding algorithms for identifying people with viral hepatitis using claims data according to different standard references
title Validation of coding algorithms for identifying people with viral hepatitis using claims data according to different standard references
title_full Validation of coding algorithms for identifying people with viral hepatitis using claims data according to different standard references
title_fullStr Validation of coding algorithms for identifying people with viral hepatitis using claims data according to different standard references
title_full_unstemmed Validation of coding algorithms for identifying people with viral hepatitis using claims data according to different standard references
title_short Validation of coding algorithms for identifying people with viral hepatitis using claims data according to different standard references
title_sort validation of coding algorithms for identifying people with viral hepatitis using claims data according to different standard references
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8897839/
https://www.ncbi.nlm.nih.gov/pubmed/35246067
http://dx.doi.org/10.1186/s12879-022-07212-w
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