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Validation of novel identification algorithms for major adverse cardiovascular events in a Japanese claims database
Predicting clinical outcomes can be difficult, particularly for life‐threatening events with a low incidence that require numerous clinical cases. Our aim was to develop and validate novel algorithms to identify major adverse cardiovascular events (MACEs) from claims databases. We developed algorith...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8029538/ https://www.ncbi.nlm.nih.gov/pubmed/33369149 http://dx.doi.org/10.1111/jch.14151 |
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author | Shima, Daisuke Ii, Yoichi Higa, Shingo Kohro, Takahide Hoshide, Satoshi Kono, Ken Fujimoto, Shigeru Niijima, Satoshi Tomitani, Naoko Kario, Kazuomi |
author_facet | Shima, Daisuke Ii, Yoichi Higa, Shingo Kohro, Takahide Hoshide, Satoshi Kono, Ken Fujimoto, Shigeru Niijima, Satoshi Tomitani, Naoko Kario, Kazuomi |
author_sort | Shima, Daisuke |
collection | PubMed |
description | Predicting clinical outcomes can be difficult, particularly for life‐threatening events with a low incidence that require numerous clinical cases. Our aim was to develop and validate novel algorithms to identify major adverse cardiovascular events (MACEs) from claims databases. We developed algorithms based on the data available in the claims database International Classification of Diseases, Tenth Revision (ICD‐10), drug prescriptions, and medical procedures. We also employed data from the claims database of Jichi Medical University Hospital, Japan, for the period between October 2012 and September 2014. In total, we randomly extracted 100 potential acute myocardial infarction cases and 200 potential stroke cases (ischemic and hemorrhagic stroke were analyzed separately) based on ICD‐10 diagnosis. An independent committee reviewed the corresponding clinical data to provide definitive diagnoses for the extracted cases. We then assessed the algorithms’ accuracy using positive predictive values (PPVs) and apparent sensitivities. The PPVs of acute myocardial infarction, ischemic stroke, and hemorrhagic stroke were low only by diagnosis (81.6% [95% CI 72.5–88.7]; 31.0% [95% CI 22.8–40.3]; and 45.5% [95% CI 34.1–57.2], respectively); however, the PPVs were elevated after adding the prescription and procedure data (87.0% [95% CI 78.3–93.1]; 44.4% [95% CI 32.7–56.6]; and 46.1% [95% CI 34.5–57.9], respectively). When we added event‐specific prescription and procedure data to the algorithms, the PPVs for each event increased to 70%–98%, with apparent sensitivities exceeding 50%. Algorithms that rely on ICD‐10 diagnosis in combination with data on specific drugs and medical procedures appear to be valid for identifying MACEs in Japanese claims databases. |
format | Online Article Text |
id | pubmed-8029538 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80295382021-12-16 Validation of novel identification algorithms for major adverse cardiovascular events in a Japanese claims database Shima, Daisuke Ii, Yoichi Higa, Shingo Kohro, Takahide Hoshide, Satoshi Kono, Ken Fujimoto, Shigeru Niijima, Satoshi Tomitani, Naoko Kario, Kazuomi J Clin Hypertens (Greenwich) New Directions of Hypertension Research in Asia Predicting clinical outcomes can be difficult, particularly for life‐threatening events with a low incidence that require numerous clinical cases. Our aim was to develop and validate novel algorithms to identify major adverse cardiovascular events (MACEs) from claims databases. We developed algorithms based on the data available in the claims database International Classification of Diseases, Tenth Revision (ICD‐10), drug prescriptions, and medical procedures. We also employed data from the claims database of Jichi Medical University Hospital, Japan, for the period between October 2012 and September 2014. In total, we randomly extracted 100 potential acute myocardial infarction cases and 200 potential stroke cases (ischemic and hemorrhagic stroke were analyzed separately) based on ICD‐10 diagnosis. An independent committee reviewed the corresponding clinical data to provide definitive diagnoses for the extracted cases. We then assessed the algorithms’ accuracy using positive predictive values (PPVs) and apparent sensitivities. The PPVs of acute myocardial infarction, ischemic stroke, and hemorrhagic stroke were low only by diagnosis (81.6% [95% CI 72.5–88.7]; 31.0% [95% CI 22.8–40.3]; and 45.5% [95% CI 34.1–57.2], respectively); however, the PPVs were elevated after adding the prescription and procedure data (87.0% [95% CI 78.3–93.1]; 44.4% [95% CI 32.7–56.6]; and 46.1% [95% CI 34.5–57.9], respectively). When we added event‐specific prescription and procedure data to the algorithms, the PPVs for each event increased to 70%–98%, with apparent sensitivities exceeding 50%. Algorithms that rely on ICD‐10 diagnosis in combination with data on specific drugs and medical procedures appear to be valid for identifying MACEs in Japanese claims databases. John Wiley and Sons Inc. 2020-12-26 /pmc/articles/PMC8029538/ /pubmed/33369149 http://dx.doi.org/10.1111/jch.14151 Text en © 2020 The Authors. The Journal of Clinical Hypertension published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | New Directions of Hypertension Research in Asia Shima, Daisuke Ii, Yoichi Higa, Shingo Kohro, Takahide Hoshide, Satoshi Kono, Ken Fujimoto, Shigeru Niijima, Satoshi Tomitani, Naoko Kario, Kazuomi Validation of novel identification algorithms for major adverse cardiovascular events in a Japanese claims database |
title | Validation of novel identification algorithms for major adverse cardiovascular events in a Japanese claims database |
title_full | Validation of novel identification algorithms for major adverse cardiovascular events in a Japanese claims database |
title_fullStr | Validation of novel identification algorithms for major adverse cardiovascular events in a Japanese claims database |
title_full_unstemmed | Validation of novel identification algorithms for major adverse cardiovascular events in a Japanese claims database |
title_short | Validation of novel identification algorithms for major adverse cardiovascular events in a Japanese claims database |
title_sort | validation of novel identification algorithms for major adverse cardiovascular events in a japanese claims database |
topic | New Directions of Hypertension Research in Asia |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8029538/ https://www.ncbi.nlm.nih.gov/pubmed/33369149 http://dx.doi.org/10.1111/jch.14151 |
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