An Algorithm That Identifies Coronary and Heart Failure Events in the Electronic Health Record

Thomas E. Kottke, MD, MSPH; Courtney Jordan Baechler, MD, MCE

Suggested citation for this article: Kottke TE, Baechler CJ. An Algorithm That Identifies Coronary and Heart Failure Events in the Electronic Health Record. Prev Chronic Dis 2013;10:120097. DOI: http://dx.doi.org/10.5888/pcd10.120097

MEDSCAPE CME

Medscape, LLC is pleased to provide online continuing medical education (CME) for this journal article, allowing clinicians the opportunity to earn CME credit.
This activity has been planned and implemented in accordance with the Essential Areas and policies of the Accreditation Council for Continuing Medical Education through the joint sponsorship of Medscape, LLC and Preventing Chronic Disease. Medscape, LLC is accredited by the ACCME to provide continuing medical education for physicians.
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Release date: February 27, 2013; Expiration date: February 27, 2014

Learning Objectives

Upon completion of this activity, participants will be able to:

Analyze recommendations regarding surveillance systems for cardiovascular disease
Compare electronic with manual health records in identifying cases of cardiovascular disease
Assess the accuracy of electronic electrocardiogram data in identifying cases of myocardial infarction
Distinguish strategies to improve the accuracy of electronic records in the surveillance of cardiovascular disease

EDITORS
Rosemarie Perrin, editor; Caran Wilbanks, editor, Preventing Chronic Disease. Disclosure: Rosemarie Perrin and Caran Wilbanks have disclosed no relevant financial relationships.
CME AUTHOR
Charles P. Vega, MD, Health Sciences Clinical Professor; Residency Director, Department of Family Medicine, University of California, Irvine. Disclosure: Charles P. Vega, MD, has disclosed no relevant financial relationships.
AUTHORS AND CREDENTIALS
Disclosures: Thomas E. Kottke, MD, MSPH; and Courtney Jordan Baechler, MD, MCE, have disclosed no relevant financial relationships.

Affiliations: Thomas E. Kottke, HealthPartners Institute for Education and Research, Minneapolis, Minnesota; Courtney Jordan Baechler, Department of Medicine, School of Public Health, University of Minnesota, Minneapolis, Minnesota.

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Abstract

Introduction
The advent of universal health care coverage in the United States and the use of electronic health records can make the medical record a disease surveillance tool. The objective of our study was to identify criteria that accurately categorize acute coronary and heart failure events by using electronic health record data exclusively so that the medical record can be used for surveillance without manual record review.
Methods
We serially compared 3 computer algorithms to manual record review. The first 2 algorithms relied on ICD-9-CM (International Classification of Diseases, 9th Revision, Clinical Modification) codes, troponin levels, electrocardiogram (ECG) data, and echocardiograph data. The third algorithm relied on a detailed coding system, Intelligent Medical Objects, Inc., (IMO) interface terminology, troponin levels, and echocardiograph data.
Results
Cohen’s κ for the initial algorithm was 0.47 (95% confidence interval [CI], 0.41–0.54). Cohen’s κ was 0.61 (95% CI, 0.55–0.68) for the second algorithm. Cohen’s κ for the third algorithm was 0.99 (95% CI, 0.98–1.00).
Conclusion
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 ICD-9-CM codes because ICD-9-CM 410.9 includes myocardial infarction with elevation of the ST segment on ECG (STEMI) and myocardial infarction without elevation of the ST segment on ECG (nSTEMI). Nearly perfect agreement can be achieved using IMO interface terminology, a more detailed coding system that tracks to ICD9, ICD10 (International Classification of Diseases, Tenth Revision, Clinical Modification), and SnoMED-CT (Systematized Nomenclature of Medicine – Clinical Terms).

ACTIVIDAD DE EMC

Un algoritmo que identifica los episodios cardiacos y de insuficiencia cardiaca en los registros de salud electrónicos

Thomas E. Kottke, MD, MSPH; Courtney Jordan Baechler, MD, MCE

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REVISADO POR EXPERTOS

Resumen

Introducción
El advenimiento de la cobertura de salud universal en los Estados Unidos y el uso de registros de salud electrónicos puede hacer que los registros médicos se conviertan en una herramienta de vigilancia de enfermedades. El objeto de nuestro estudio fue identificar los fundamentos que categorizan los episodios cardiacos y de insuficiencia cardiaca agudos de manera precisa mediante el uso exclusivo de los datos contenidos en los registros de salud electrónicos, de manera tal que los registros médicos se puedan utilizar para los fines de vigilancia de enfermedades sin que se haga una revisión manual.
Métodos
Hicimos una comparación en serie de 3 algoritmos computarizados y un análisis manual de los registros. Los primeros 2 algoritmos se basaron en los códigos ICD-9-CM (Clasificación Internacional de Enfermedades, Novena Revisión. Modificación Clínica), los niveles de troponina, los datos obtenidos de electrocardiogramas (ECG) y de ecocardiografías. El tercer algoritmo se basó en un sistema detallado de codificación, terminología de interfaz de Intelligent Medical Objects, Inc., (IMO), los niveles de troponina y los datos obtenidos de ecocardiografías.
Resultados
El coeficiente κ de Cohen para el algoritmo original fue 0.47 (95 % del intervalo de confianza [CI], 0.41-0.54). El coeficiente κ de Cohen fue 0.61 (95 % CI, 0.55–0.68) para el segundo algoritmo. El coeficiente κ de Cohen para el tercer algoritmo fue 0.99 (95 % CI, 0.98–1.00).
Conclusión
Para categorizar las enfermedades cardiacas y la insuficiencia cardiaca bastan los datos de los registros de salud electrónicos sin la necesidad de hacer una revisión manual. Sin embargo, solamente se puede lograr una concordancia moderada en el análisis de los registros médicos si la clasificación se basa en los códigos ICD-9-CM de 4 dígitos debido a que el código 410.9 del ICD-9-CM incluye el infarto de miocardio con elevación del segmento ST en el ECG (STEMI) y el infarto de miocardio sin elevación del segmento ST en el ECG (nSTEMI). Se puede lograr una concordancia casi exacta con la terminología de interfaz de IMO, un sistema de codificación más detallado que se basa en el ICD9, el ICD 10 (Clasificación Internacional de Enfermedades, Décima Revisión. Modificación Clínica) y el SnoMED-CT (Nomenclatura sistematizada de medicina - Términos clínicos).