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Determining diagnosis date of diabetes using structured electronic health record (EHR) data: the SEARCH for diabetes in youth study
BACKGROUND: Disease surveillance of diabetes among youth has relied mainly upon manual chart review. However, increasingly available structured electronic health record (EHR) data have been shown to yield accurate determinations of diabetes status and type. Validated algorithms to determine date of...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8502379/ https://www.ncbi.nlm.nih.gov/pubmed/34629073 http://dx.doi.org/10.1186/s12874-021-01394-8 |
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author | Lenoir, Kristin M. Wagenknecht, Lynne E. Divers, Jasmin Casanova, Ramon Dabelea, Dana Saydah, Sharon Pihoker, Catherine Liese, Angela D. Standiford, Debra Hamman, Richard Wells, Brian J. |
author_facet | Lenoir, Kristin M. Wagenknecht, Lynne E. Divers, Jasmin Casanova, Ramon Dabelea, Dana Saydah, Sharon Pihoker, Catherine Liese, Angela D. Standiford, Debra Hamman, Richard Wells, Brian J. |
author_sort | Lenoir, Kristin M. |
collection | PubMed |
description | BACKGROUND: Disease surveillance of diabetes among youth has relied mainly upon manual chart review. However, increasingly available structured electronic health record (EHR) data have been shown to yield accurate determinations of diabetes status and type. Validated algorithms to determine date of diabetes diagnosis are lacking. The objective of this work is to validate two EHR-based algorithms to determine date of diagnosis of diabetes. METHODS: A rule-based ICD-10 algorithm identified youth with diabetes from structured EHR data over the period of 2009 through 2017 within three children’s hospitals that participate in the SEARCH for Diabetes in Youth Study: Cincinnati Children’s Hospital, Cincinnati, OH, Seattle Children’s Hospital, Seattle, WA, and Children’s Hospital Colorado, Denver, CO. Previous research and a multidisciplinary team informed the creation of two algorithms based upon structured EHR data to determine date of diagnosis among diabetes cases. An ICD-code algorithm was defined by the year of occurrence of a second ICD-9 or ICD-10 diabetes code. A multiple-criteria algorithm consisted of the year of first occurrence of any of the following: diabetes-related ICD code, elevated glucose, elevated HbA1c, or diabetes medication. We assessed algorithm performance by percent agreement with a gold standard date of diagnosis determined by chart review. RESULTS: Among 3777 cases, both algorithms demonstrated high agreement with true diagnosis year and differed in classification (p = 0.006): 86.5% agreement for the ICD code algorithm and 85.9% agreement for the multiple-criteria algorithm. Agreement was high for both type 1 and type 2 cases for the ICD code algorithm. Performance improved over time. CONCLUSIONS: Year of occurrence of the second ICD diabetes-related code in the EHR yields an accurate diagnosis date within these pediatric hospital systems. This may lead to increased efficiency and sustainability of surveillance methods for incidence of diabetes among youth. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01394-8. |
format | Online Article Text |
id | pubmed-8502379 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-85023792021-10-20 Determining diagnosis date of diabetes using structured electronic health record (EHR) data: the SEARCH for diabetes in youth study Lenoir, Kristin M. Wagenknecht, Lynne E. Divers, Jasmin Casanova, Ramon Dabelea, Dana Saydah, Sharon Pihoker, Catherine Liese, Angela D. Standiford, Debra Hamman, Richard Wells, Brian J. BMC Med Res Methodol Research BACKGROUND: Disease surveillance of diabetes among youth has relied mainly upon manual chart review. However, increasingly available structured electronic health record (EHR) data have been shown to yield accurate determinations of diabetes status and type. Validated algorithms to determine date of diabetes diagnosis are lacking. The objective of this work is to validate two EHR-based algorithms to determine date of diagnosis of diabetes. METHODS: A rule-based ICD-10 algorithm identified youth with diabetes from structured EHR data over the period of 2009 through 2017 within three children’s hospitals that participate in the SEARCH for Diabetes in Youth Study: Cincinnati Children’s Hospital, Cincinnati, OH, Seattle Children’s Hospital, Seattle, WA, and Children’s Hospital Colorado, Denver, CO. Previous research and a multidisciplinary team informed the creation of two algorithms based upon structured EHR data to determine date of diagnosis among diabetes cases. An ICD-code algorithm was defined by the year of occurrence of a second ICD-9 or ICD-10 diabetes code. A multiple-criteria algorithm consisted of the year of first occurrence of any of the following: diabetes-related ICD code, elevated glucose, elevated HbA1c, or diabetes medication. We assessed algorithm performance by percent agreement with a gold standard date of diagnosis determined by chart review. RESULTS: Among 3777 cases, both algorithms demonstrated high agreement with true diagnosis year and differed in classification (p = 0.006): 86.5% agreement for the ICD code algorithm and 85.9% agreement for the multiple-criteria algorithm. Agreement was high for both type 1 and type 2 cases for the ICD code algorithm. Performance improved over time. CONCLUSIONS: Year of occurrence of the second ICD diabetes-related code in the EHR yields an accurate diagnosis date within these pediatric hospital systems. This may lead to increased efficiency and sustainability of surveillance methods for incidence of diabetes among youth. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01394-8. BioMed Central 2021-10-10 /pmc/articles/PMC8502379/ /pubmed/34629073 http://dx.doi.org/10.1186/s12874-021-01394-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Lenoir, Kristin M. Wagenknecht, Lynne E. Divers, Jasmin Casanova, Ramon Dabelea, Dana Saydah, Sharon Pihoker, Catherine Liese, Angela D. Standiford, Debra Hamman, Richard Wells, Brian J. Determining diagnosis date of diabetes using structured electronic health record (EHR) data: the SEARCH for diabetes in youth study |
title | Determining diagnosis date of diabetes using structured electronic health record (EHR) data: the SEARCH for diabetes in youth study |
title_full | Determining diagnosis date of diabetes using structured electronic health record (EHR) data: the SEARCH for diabetes in youth study |
title_fullStr | Determining diagnosis date of diabetes using structured electronic health record (EHR) data: the SEARCH for diabetes in youth study |
title_full_unstemmed | Determining diagnosis date of diabetes using structured electronic health record (EHR) data: the SEARCH for diabetes in youth study |
title_short | Determining diagnosis date of diabetes using structured electronic health record (EHR) data: the SEARCH for diabetes in youth study |
title_sort | determining diagnosis date of diabetes using structured electronic health record (ehr) data: the search for diabetes in youth study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8502379/ https://www.ncbi.nlm.nih.gov/pubmed/34629073 http://dx.doi.org/10.1186/s12874-021-01394-8 |
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