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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Published in:Clinical Epidemiology
Main Authors: Reges,Orna, Weinberg,Hagay, Hoshen,Moshe, Greenland,Philip, Rayyan-Assi,Hana'a, Avgil Tsadok,Meytal, Bachrach,Asaf, Balicer,Ran, Leibowitz,Morton, Haim,Moti
Format: Article in Journal/Newspaper
Language:English
Published: Dove Press 2020
Subjects:
Online Access:https://www.dovepress.com/combining-inpatient-and-outpatient-data-for-diagnosis-of-non-valvular--peer-reviewed-fulltext-article-CLEP
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spelling ftdovepress:oai:dovepress.com/53931 2023-05-15T16:29:57+02:00 Combining Inpatient and Outpatient Data for Diagnosis of Non-Valvular Atrial Fibrillation Using Electronic Health Records: A Validation Study Reges,Orna Weinberg,Hagay Hoshen,Moshe Greenland,Philip Rayyan-Assi,Hana'a Avgil Tsadok,Meytal Bachrach,Asaf Balicer,Ran Leibowitz,Morton Haim,Moti 2020-05-20 text/html https://www.dovepress.com/combining-inpatient-and-outpatient-data-for-diagnosis-of-non-valvular--peer-reviewed-fulltext-article-CLEP en eng Dove Press info:eu-repo/semantics/altIdentifier/doi/10.2147/CLEP.S230677 https://www.dovepress.com/combining-inpatient-and-outpatient-data-for-diagnosis-of-non-valvular--peer-reviewed-fulltext-article-CLEP info:eu-repo/semantics/openAccess Clinical Epidemiology Original Research info:eu-repo/semantics/article 2020 ftdovepress https://doi.org/10.2147/CLEP.S230677 2022-12-27T22:51:01Z 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 Dove Medical Press Greenland New Zealand Morton ENVELOPE(-61.220,-61.220,-62.697,-62.697) Saba ENVELOPE(149.417,149.417,66.617,66.617) Clinical Epidemiology Volume 12 477 483
institution Open Polar
collection Dove Medical Press
op_collection_id ftdovepress
language English
topic Clinical Epidemiology
spellingShingle Clinical Epidemiology
Reges,Orna
Weinberg,Hagay
Hoshen,Moshe
Greenland,Philip
Rayyan-Assi,Hana'a
Avgil Tsadok,Meytal
Bachrach,Asaf
Balicer,Ran
Leibowitz,Morton
Haim,Moti
Combining Inpatient and Outpatient Data for Diagnosis of Non-Valvular Atrial Fibrillation Using Electronic Health Records: A Validation Study
topic_facet Clinical Epidemiology
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,Orna
Weinberg,Hagay
Hoshen,Moshe
Greenland,Philip
Rayyan-Assi,Hana'a
Avgil Tsadok,Meytal
Bachrach,Asaf
Balicer,Ran
Leibowitz,Morton
Haim,Moti
author_facet Reges,Orna
Weinberg,Hagay
Hoshen,Moshe
Greenland,Philip
Rayyan-Assi,Hana'a
Avgil Tsadok,Meytal
Bachrach,Asaf
Balicer,Ran
Leibowitz,Morton
Haim,Moti
author_sort Reges,Orna
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 Press
publishDate 2020
url https://www.dovepress.com/combining-inpatient-and-outpatient-data-for-diagnosis-of-non-valvular--peer-reviewed-fulltext-article-CLEP
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container_title Clinical Epidemiology
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