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Identification of people with acquired hemophilia in a large electronic health record database
BACKGROUND: Electronic health records (EHRs) can provide insights into diagnoses, treatment patterns, and clinical outcomes. Acquired hemophilia (AH) is an ultrarare bleeding disorder characterized by factor VIII inhibiting autoantibodies. AIM: To identify patients with AH using an EHR database. MET...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5529096/ https://www.ncbi.nlm.nih.gov/pubmed/28769599 http://dx.doi.org/10.2147/JBM.S136060 |
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author | Wang, Michael Cyhaniuk, Anissa Cooper, David L Iyer, Neeraj N |
author_facet | Wang, Michael Cyhaniuk, Anissa Cooper, David L Iyer, Neeraj N |
author_sort | Wang, Michael |
collection | PubMed |
description | BACKGROUND: Electronic health records (EHRs) can provide insights into diagnoses, treatment patterns, and clinical outcomes. Acquired hemophilia (AH) is an ultrarare bleeding disorder characterized by factor VIII inhibiting autoantibodies. AIM: To identify patients with AH using an EHR database. METHODS: Records were accessed from a large EHR database (Humedica) between January 1, 2007 and July 31, 2013. Broad selection criteria were applied using the International Classification of Diseases, Ninth Revision, clinical modification (ICD-9-CM) code for intrinsic circulating anticoagulants (286.5 and all subcodes) and confirmation of records 6 months before and 12 months after the first diagnosis. Additional selection criteria included mention of “bleeding” within physician notes identified via natural language processing output and a normal prothrombin time and prolonged activated partial thromboplastin time. RESULTS: Of 6,348 patients with a diagnosis code of 286.5 or any subcodes, 16 males and 15 females met the selection criteria. The most common bleeding locations reported was gastrointestinal (23%), vaginal (16%), and endocrine (13%). A wide range of comorbidities was reported. Natural language processing identified chart note mention of “hemophilia” in 3 patients (10%), “bruise” in 15 patients (48%), and “pain” in all 31 patients. No patients received a prescription for approved/recommended AH treatments. Four patient cases were reviewed to validate whether the identified cohort had AH; each patient had bleeding symptoms and a normal prothrombin time and prolonged activated partial thromboplastin time, although none received hemostatic treatments. CONCLUSION: In ultrarare disorders, ICD-9-CM coding alone may be insufficient to identify patient cohorts; multimodal analysis combined with in-depth reviews of physician notes may be more effective. |
format | Online Article Text |
id | pubmed-5529096 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-55290962017-08-02 Identification of people with acquired hemophilia in a large electronic health record database Wang, Michael Cyhaniuk, Anissa Cooper, David L Iyer, Neeraj N J Blood Med Original Research BACKGROUND: Electronic health records (EHRs) can provide insights into diagnoses, treatment patterns, and clinical outcomes. Acquired hemophilia (AH) is an ultrarare bleeding disorder characterized by factor VIII inhibiting autoantibodies. AIM: To identify patients with AH using an EHR database. METHODS: Records were accessed from a large EHR database (Humedica) between January 1, 2007 and July 31, 2013. Broad selection criteria were applied using the International Classification of Diseases, Ninth Revision, clinical modification (ICD-9-CM) code for intrinsic circulating anticoagulants (286.5 and all subcodes) and confirmation of records 6 months before and 12 months after the first diagnosis. Additional selection criteria included mention of “bleeding” within physician notes identified via natural language processing output and a normal prothrombin time and prolonged activated partial thromboplastin time. RESULTS: Of 6,348 patients with a diagnosis code of 286.5 or any subcodes, 16 males and 15 females met the selection criteria. The most common bleeding locations reported was gastrointestinal (23%), vaginal (16%), and endocrine (13%). A wide range of comorbidities was reported. Natural language processing identified chart note mention of “hemophilia” in 3 patients (10%), “bruise” in 15 patients (48%), and “pain” in all 31 patients. No patients received a prescription for approved/recommended AH treatments. Four patient cases were reviewed to validate whether the identified cohort had AH; each patient had bleeding symptoms and a normal prothrombin time and prolonged activated partial thromboplastin time, although none received hemostatic treatments. CONCLUSION: In ultrarare disorders, ICD-9-CM coding alone may be insufficient to identify patient cohorts; multimodal analysis combined with in-depth reviews of physician notes may be more effective. Dove Medical Press 2017-07-19 /pmc/articles/PMC5529096/ /pubmed/28769599 http://dx.doi.org/10.2147/JBM.S136060 Text en © 2017 Wang et al. 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. |
spellingShingle | Original Research Wang, Michael Cyhaniuk, Anissa Cooper, David L Iyer, Neeraj N Identification of people with acquired hemophilia in a large electronic health record database |
title | Identification of people with acquired hemophilia in a large electronic health record database |
title_full | Identification of people with acquired hemophilia in a large electronic health record database |
title_fullStr | Identification of people with acquired hemophilia in a large electronic health record database |
title_full_unstemmed | Identification of people with acquired hemophilia in a large electronic health record database |
title_short | Identification of people with acquired hemophilia in a large electronic health record database |
title_sort | identification of people with acquired hemophilia in a large electronic health record database |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5529096/ https://www.ncbi.nlm.nih.gov/pubmed/28769599 http://dx.doi.org/10.2147/JBM.S136060 |
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