Assessing the concordance of clinical classification criteria for lupus between electronic health records and a physician curated registry

Theresa L. Walunas; Anika S. Ghosh; Jennifer A. Pacheco; Kathryn L. Jackson; Anh H. Chung; Daniel L. Erickson; Karen Mancera-Cuevas; Rosalind Ramsey-Goldman; Abel N. Kho

doi:10.3233/SHTI190487

Assessing the concordance of clinical classification criteria for lupus between electronic health records and a physician curated registry

Theresa L. Walunas^*, Anika S. Ghosh, Jennifer A. Pacheco, Kathryn L. Jackson, Anh H. Chung, Daniel L. Erickson, Karen Mancera-Cuevas, Rosalind Ramsey-Goldman, Abel N. Kho

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We developed a computable phenotype for systemic lupus erythematosus (SLE) based on the Systemic Lupus International Collaborative Clinics clinical classification criteria set for SLE. We evaluated the phenotype over registry and EHR data for the same patient population to determine concordance of criteria detected in both datasets and to assess which types of structured data detected individual classification criteria. We identified a concordance of 68% between registry and EHR data relying solely on structured data.

Original language	English (US)
Title of host publication	MEDINFO 2019
Subtitle of host publication	Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics
Editors	Brigitte Seroussi, Lucila Ohno-Machado, Lucila Ohno-Machado, Brigitte Seroussi
Publisher	IOS Press
Pages	1466-1467
Number of pages	2
ISBN (Electronic)	9781643680026
DOIs	https://doi.org/10.3233/SHTI190487
State	Published - Aug 21 2019
Event	17th World Congress on Medical and Health Informatics, MEDINFO 2019 - Lyon, France Duration: Aug 25 2019 → Aug 30 2019

Publication series

Name	Studies in Health Technology and Informatics
Volume	264
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	17th World Congress on Medical and Health Informatics, MEDINFO 2019
Country/Territory	France
City	Lyon
Period	8/25/19 → 8/30/19

Funding

Research reported in this publication was supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health under Award Number R21AR072263. Development of the CLD database were supported by grant P60 AR064464 and P30 AR072579.

Keywords

Electronic health records
Phenotype
Systemic lupus erythematosus

ASJC Scopus subject areas

Biomedical Engineering
Health Informatics
Health Information Management

Access to Document

10.3233/SHTI190487

Cite this

Walunas, T. L., Ghosh, A. S., Pacheco, J. A., Jackson, K. L., Chung, A. H., Erickson, D. L., Mancera-Cuevas, K., Ramsey-Goldman, R., & Kho, A. N. (2019). Assessing the concordance of clinical classification criteria for lupus between electronic health records and a physician curated registry. In B. Seroussi, L. Ohno-Machado, L. Ohno-Machado, & B. Seroussi (Eds.), MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics (pp. 1466-1467). (Studies in Health Technology and Informatics; Vol. 264). IOS Press. https://doi.org/10.3233/SHTI190487

Walunas, Theresa L. ; Ghosh, Anika S. ; Pacheco, Jennifer A. et al. / Assessing the concordance of clinical classification criteria for lupus between electronic health records and a physician curated registry. MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. editor / Brigitte Seroussi ; Lucila Ohno-Machado ; Lucila Ohno-Machado ; Brigitte Seroussi. IOS Press, 2019. pp. 1466-1467 (Studies in Health Technology and Informatics).

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abstract = "We developed a computable phenotype for systemic lupus erythematosus (SLE) based on the Systemic Lupus International Collaborative Clinics clinical classification criteria set for SLE. We evaluated the phenotype over registry and EHR data for the same patient population to determine concordance of criteria detected in both datasets and to assess which types of structured data detected individual classification criteria. We identified a concordance of 68% between registry and EHR data relying solely on structured data.",

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Walunas, TL, Ghosh, AS, Pacheco, JA, Jackson, KL, Chung, AH, Erickson, DL, Mancera-Cuevas, K, Ramsey-Goldman, R & Kho, AN 2019, Assessing the concordance of clinical classification criteria for lupus between electronic health records and a physician curated registry. in B Seroussi, L Ohno-Machado, L Ohno-Machado & B Seroussi (eds), MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. Studies in Health Technology and Informatics, vol. 264, IOS Press, pp. 1466-1467, 17th World Congress on Medical and Health Informatics, MEDINFO 2019, Lyon, France, 8/25/19. https://doi.org/10.3233/SHTI190487

Assessing the concordance of clinical classification criteria for lupus between electronic health records and a physician curated registry. / Walunas, Theresa L.; Ghosh, Anika S.; Pacheco, Jennifer A. et al.
MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. ed. / Brigitte Seroussi; Lucila Ohno-Machado; Lucila Ohno-Machado; Brigitte Seroussi. IOS Press, 2019. p. 1466-1467 (Studies in Health Technology and Informatics; Vol. 264).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Walunas, Theresa L.

AU - Ghosh, Anika S.

AU - Pacheco, Jennifer A.

AU - Jackson, Kathryn L.

AU - Chung, Anh H.

AU - Erickson, Daniel L.

AU - Mancera-Cuevas, Karen

AU - Ramsey-Goldman, Rosalind

AU - Kho, Abel N.

N1 - Publisher Copyright: © 2019 International Medical Informatics Association (IMIA) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).

PY - 2019/8/21

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N2 - We developed a computable phenotype for systemic lupus erythematosus (SLE) based on the Systemic Lupus International Collaborative Clinics clinical classification criteria set for SLE. We evaluated the phenotype over registry and EHR data for the same patient population to determine concordance of criteria detected in both datasets and to assess which types of structured data detected individual classification criteria. We identified a concordance of 68% between registry and EHR data relying solely on structured data.

AB - We developed a computable phenotype for systemic lupus erythematosus (SLE) based on the Systemic Lupus International Collaborative Clinics clinical classification criteria set for SLE. We evaluated the phenotype over registry and EHR data for the same patient population to determine concordance of criteria detected in both datasets and to assess which types of structured data detected individual classification criteria. We identified a concordance of 68% between registry and EHR data relying solely on structured data.

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Walunas TL, Ghosh AS, Pacheco JA, Jackson KL, Chung AH, Erickson DL et al. Assessing the concordance of clinical classification criteria for lupus between electronic health records and a physician curated registry. In Seroussi B, Ohno-Machado L, Ohno-Machado L, Seroussi B, editors, MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics. IOS Press. 2019. p. 1466-1467. (Studies in Health Technology and Informatics). doi: 10.3233/SHTI190487

Assessing the concordance of clinical classification criteria for lupus between electronic health records and a physician curated registry

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