Combining Inpatient and Outpatient Data for Diagnosis of Non-Valvular Atrial Fibrillation Using Electronic Health Records: A Validation Study
Orna Reges,1,2,* Hagay Weinberg,3,4,* Moshe Hoshen,1,5 Philip Greenland,2 Hana’a Rayyan-Assi,1 Meytal Avgil Tsadok,1 Asaf Bachrach,1 Ran Balicer,1,6 Morton Leibowitz,1 Moti Haim7,8 1Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel; 2Department of Preventive Medicine, Northwestern...
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ftdoajarticles:oai:doaj.org/article:7c2201ff751240cc90a65b6b6567d7a7 2023-05-15T16:30:10+02:00 Combining Inpatient and Outpatient Data for Diagnosis of Non-Valvular Atrial Fibrillation Using Electronic Health Records: A Validation Study Reges O Weinberg H Hoshen M Greenland P Rayyan-Assi H Avgil Tsadok M Bachrach A Balicer R Leibowitz M Haim M 2020-05-01T00:00:00Z https://doaj.org/article/7c2201ff751240cc90a65b6b6567d7a7 EN eng Dove Medical Press https://www.dovepress.com/combining-inpatient-and-outpatient-data-for-diagnosis-of-non-valvular--peer-reviewed-article-CLEP https://doaj.org/toc/1179-1349 1179-1349 https://doaj.org/article/7c2201ff751240cc90a65b6b6567d7a7 Clinical Epidemiology, Vol Volume 12, Pp 477-483 (2020) atrial fibrillation validation electronic health records Infectious and parasitic diseases RC109-216 article 2020 ftdoajarticles 2022-12-31T13:16:08Z Orna Reges,1,2,* Hagay Weinberg,3,4,* Moshe Hoshen,1,5 Philip Greenland,2 Hana’a Rayyan-Assi,1 Meytal Avgil Tsadok,1 Asaf Bachrach,1 Ran Balicer,1,6 Morton Leibowitz,1 Moti Haim7,8 1Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel; 2Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; 3Internal Medicine Department, Meir Medical Center, Kfar-Saba, Israel; 4Department of Medicine, MidCentral District Health Board, Palmerston-North, New Zealand; 5National Information Systems, Computational Authority, Ministry of Health, Jerusalem, Isarel; 6Department of Epidemiology, Ben-Gurion University of the Negev, Beer-Sheva, Israel; 7Department of Cardiology, Soroka University Medical Center, Beer Sheva, Israel; 8Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, Israel*These authors contributed equally to this workCorrespondence: Orna RegesDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 North Lake Shore Drive, Suite 1400, Chicago, IL 60611, USAEmail orna.reges@gmail.comPurpose: Previous studies have demonstrated differences in atrial fibrillation (AF) detection based on data from hospital sources without data from outpatient sources. We investigated the detection of documented diagnoses of non-valvular AF in a large Israeli health-care organization using electronic health record data from multiple sources.Patients and Methods: This was an open-chart validation study. Three distinct algorithms for identifying AF in electronic health records, differing in the source of their International Classification of Diseases, Ninth Revision code and use of the associated free text, were defined. Algorithm 1 incorporated inpatient data with outpatient data and the associated free text. Algorithm 2 incorporated inpatient and outpatient data regardless of the free text associated with AF diagnosis. Algorithm 3 used only inpatient data source. These algorithms were compared to a gold standard and their ... Article in Journal/Newspaper Greenland Directory of Open Access Journals: DOAJ Articles Greenland New Zealand Morton ENVELOPE(-61.220,-61.220,-62.697,-62.697) Saba ENVELOPE(149.417,149.417,66.617,66.617) |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
atrial fibrillation validation electronic health records Infectious and parasitic diseases RC109-216 |
spellingShingle |
atrial fibrillation validation electronic health records Infectious and parasitic diseases RC109-216 Reges O Weinberg H Hoshen M Greenland P Rayyan-Assi H Avgil Tsadok M Bachrach A Balicer R Leibowitz M Haim M Combining Inpatient and Outpatient Data for Diagnosis of Non-Valvular Atrial Fibrillation Using Electronic Health Records: A Validation Study |
topic_facet |
atrial fibrillation validation electronic health records Infectious and parasitic diseases RC109-216 |
description |
Orna Reges,1,2,* Hagay Weinberg,3,4,* Moshe Hoshen,1,5 Philip Greenland,2 Hana’a Rayyan-Assi,1 Meytal Avgil Tsadok,1 Asaf Bachrach,1 Ran Balicer,1,6 Morton Leibowitz,1 Moti Haim7,8 1Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel; 2Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; 3Internal Medicine Department, Meir Medical Center, Kfar-Saba, Israel; 4Department of Medicine, MidCentral District Health Board, Palmerston-North, New Zealand; 5National Information Systems, Computational Authority, Ministry of Health, Jerusalem, Isarel; 6Department of Epidemiology, Ben-Gurion University of the Negev, Beer-Sheva, Israel; 7Department of Cardiology, Soroka University Medical Center, Beer Sheva, Israel; 8Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheva, Israel*These authors contributed equally to this workCorrespondence: Orna RegesDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 North Lake Shore Drive, Suite 1400, Chicago, IL 60611, USAEmail orna.reges@gmail.comPurpose: Previous studies have demonstrated differences in atrial fibrillation (AF) detection based on data from hospital sources without data from outpatient sources. We investigated the detection of documented diagnoses of non-valvular AF in a large Israeli health-care organization using electronic health record data from multiple sources.Patients and Methods: This was an open-chart validation study. Three distinct algorithms for identifying AF in electronic health records, differing in the source of their International Classification of Diseases, Ninth Revision code and use of the associated free text, were defined. Algorithm 1 incorporated inpatient data with outpatient data and the associated free text. Algorithm 2 incorporated inpatient and outpatient data regardless of the free text associated with AF diagnosis. Algorithm 3 used only inpatient data source. These algorithms were compared to a gold standard and their ... |
format |
Article in Journal/Newspaper |
author |
Reges O Weinberg H Hoshen M Greenland P Rayyan-Assi H Avgil Tsadok M Bachrach A Balicer R Leibowitz M Haim M |
author_facet |
Reges O Weinberg H Hoshen M Greenland P Rayyan-Assi H Avgil Tsadok M Bachrach A Balicer R Leibowitz M Haim M |
author_sort |
Reges O |
title |
Combining Inpatient and Outpatient Data for Diagnosis of Non-Valvular Atrial Fibrillation Using Electronic Health Records: A Validation Study |
title_short |
Combining Inpatient and Outpatient Data for Diagnosis of Non-Valvular Atrial Fibrillation Using Electronic Health Records: A Validation Study |
title_full |
Combining Inpatient and Outpatient Data for Diagnosis of Non-Valvular Atrial Fibrillation Using Electronic Health Records: A Validation Study |
title_fullStr |
Combining Inpatient and Outpatient Data for Diagnosis of Non-Valvular Atrial Fibrillation Using Electronic Health Records: A Validation Study |
title_full_unstemmed |
Combining Inpatient and Outpatient Data for Diagnosis of Non-Valvular Atrial Fibrillation Using Electronic Health Records: A Validation Study |
title_sort |
combining inpatient and outpatient data for diagnosis of non-valvular atrial fibrillation using electronic health records: a validation study |
publisher |
Dove Medical Press |
publishDate |
2020 |
url |
https://doaj.org/article/7c2201ff751240cc90a65b6b6567d7a7 |
long_lat |
ENVELOPE(-61.220,-61.220,-62.697,-62.697) ENVELOPE(149.417,149.417,66.617,66.617) |
geographic |
Greenland New Zealand Morton Saba |
geographic_facet |
Greenland New Zealand Morton Saba |
genre |
Greenland |
genre_facet |
Greenland |
op_source |
Clinical Epidemiology, Vol Volume 12, Pp 477-483 (2020) |
op_relation |
https://www.dovepress.com/combining-inpatient-and-outpatient-data-for-diagnosis-of-non-valvular--peer-reviewed-article-CLEP https://doaj.org/toc/1179-1349 1179-1349 https://doaj.org/article/7c2201ff751240cc90a65b6b6567d7a7 |
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1766019886627160064 |