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An Algorithm That Identifies Coronary and Heart Failure Events In The Electronic Health Record

OBJECTIVE: The objective of this project was to identify criteria that accurately categorize acute coronary and heart failure events exclusively with electronic health record data so that the medical record can be used for surveillance without manual record review. INTRODUCTION: Surveillance to trac...

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Autores principales: Jaranilla, Jawali, Kottke, Thomas E., Baechler, Courtney J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: University of Illinois at Chicago Library 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3692808/
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author Jaranilla, Jawali
Kottke, Thomas E.
Baechler, Courtney J.
author_facet Jaranilla, Jawali
Kottke, Thomas E.
Baechler, Courtney J.
author_sort Jaranilla, Jawali
collection PubMed
description OBJECTIVE: The objective of this project was to identify criteria that accurately categorize acute coronary and heart failure events exclusively with electronic health record data so that the medical record can be used for surveillance without manual record review. INTRODUCTION: Surveillance to track the incidence, prevalence and treatment of disease is a fundamental task of public health. The advent of universal health care coverage in the United States and electronic health records could make the medical record a valuable disease surveillance tool. This can only happen, however, if the necessary data can be extracted from the medical record without manual review. METHODS: We serially compared 3 different computer algorithms to manual record review. The first two algorithms relied on ICD9CM codes, troponin levels, ECG data and echocardiographic data. The 3rd algorithm relied on a very detailed coding system, IMO statements, troponin levels and echocardiographic data. RESULTS: Cohen’s Kappa for the initial algorithm was 0.47 (95%CI 0.41–0.54). Cohen’s Kappa was 0.61 (95%CI 0.55–0.68) for the second algorithm. Cohen’s Kappa for the third algorithm was 0.99 (95%CI 0.98–1.00). CONCLUSIONS: We conclude that electronic medical record data are sufficient to categorize coronary heart disease and heart failure events without manual record review. However, only moderate agreement with medical record review can be achieved when the classification is based on 4-digit ICD9CM codes because ICD9CM 410.9 includes myocardial infarction with ST elevation (STEMI) and myocardial infarction without ST elevation (nSTEMI). Nearly perfect agreement can be achieved using IMO statements, a more detailed coding system that tracks to ICD9, ICD10 and SnoMED-CT. IMO statements are available in many electronic medical record systems.
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spelling pubmed-36928082013-06-26 An Algorithm That Identifies Coronary and Heart Failure Events In The Electronic Health Record Jaranilla, Jawali Kottke, Thomas E. Baechler, Courtney J. Online J Public Health Inform ISDS 2012 Conference Abstracts OBJECTIVE: The objective of this project was to identify criteria that accurately categorize acute coronary and heart failure events exclusively with electronic health record data so that the medical record can be used for surveillance without manual record review. INTRODUCTION: Surveillance to track the incidence, prevalence and treatment of disease is a fundamental task of public health. The advent of universal health care coverage in the United States and electronic health records could make the medical record a valuable disease surveillance tool. This can only happen, however, if the necessary data can be extracted from the medical record without manual review. METHODS: We serially compared 3 different computer algorithms to manual record review. The first two algorithms relied on ICD9CM codes, troponin levels, ECG data and echocardiographic data. The 3rd algorithm relied on a very detailed coding system, IMO statements, troponin levels and echocardiographic data. RESULTS: Cohen’s Kappa for the initial algorithm was 0.47 (95%CI 0.41–0.54). Cohen’s Kappa was 0.61 (95%CI 0.55–0.68) for the second algorithm. Cohen’s Kappa for the third algorithm was 0.99 (95%CI 0.98–1.00). CONCLUSIONS: We conclude that electronic medical record data are sufficient to categorize coronary heart disease and heart failure events without manual record review. However, only moderate agreement with medical record review can be achieved when the classification is based on 4-digit ICD9CM codes because ICD9CM 410.9 includes myocardial infarction with ST elevation (STEMI) and myocardial infarction without ST elevation (nSTEMI). Nearly perfect agreement can be achieved using IMO statements, a more detailed coding system that tracks to ICD9, ICD10 and SnoMED-CT. IMO statements are available in many electronic medical record systems. University of Illinois at Chicago Library 2013-04-04 /pmc/articles/PMC3692808/ Text en ©2013 the author(s) http://www.uic.edu/htbin/cgiwrap/bin/ojs/index.php/ojphi/about/submissions#copyrightNotice This is an Open Access article. Authors own copyright of their articles appearing in the Online Journal of Public Health Informatics. Readers may copy articles without permission of the copyright owner(s), as long as the author and OJPHI are acknowledged in the copy and the copy is used for educational, not-for-profit purposes.
spellingShingle ISDS 2012 Conference Abstracts
Jaranilla, Jawali
Kottke, Thomas E.
Baechler, Courtney J.
An Algorithm That Identifies Coronary and Heart Failure Events In The Electronic Health Record
title An Algorithm That Identifies Coronary and Heart Failure Events In The Electronic Health Record
title_full An Algorithm That Identifies Coronary and Heart Failure Events In The Electronic Health Record
title_fullStr An Algorithm That Identifies Coronary and Heart Failure Events In The Electronic Health Record
title_full_unstemmed An Algorithm That Identifies Coronary and Heart Failure Events In The Electronic Health Record
title_short An Algorithm That Identifies Coronary and Heart Failure Events In The Electronic Health Record
title_sort algorithm that identifies coronary and heart failure events in the electronic health record
topic ISDS 2012 Conference Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3692808/
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