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How well can familial hypercholesterolemia be identified in an electronic health record database?
BACKGROUND: Familial hypercholesterolemia (FH) is a condition characterized by high cholesterol levels and increased risk for coronary heart disease (CHD) that often goes undiagnosed. The Dutch Lipid Network Criteria (DLNC) are used to identify FH in clinical settings via physical examination, perso...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6241698/ https://www.ncbi.nlm.nih.gov/pubmed/30532597 http://dx.doi.org/10.2147/CLEP.S176853 |
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author | Mues, Katherine E Bogdanov, Alina N Monda, Keri L Yedigarova, Larisa Liede, Alexander Kallenbach, Lee |
author_facet | Mues, Katherine E Bogdanov, Alina N Monda, Keri L Yedigarova, Larisa Liede, Alexander Kallenbach, Lee |
author_sort | Mues, Katherine E |
collection | PubMed |
description | BACKGROUND: Familial hypercholesterolemia (FH) is a condition characterized by high cholesterol levels and increased risk for coronary heart disease (CHD) that often goes undiagnosed. The Dutch Lipid Network Criteria (DLNC) are used to identify FH in clinical settings via physical examination, personal and family history of CHD, in addition to the presence of deleterious mutations of the LDLR, ApoB, and PCSK9 genes. Agreement between clinical and genetic diagnosis of FH varies. While an ICD diagnosis code was not available for coding FH until 2016, Systematized Nomenclature of Medicine (SNOMED) clinical concept codes, including genetic diagnoses, for FH have been utilized in electronic health records (EHRs). OBJECTIVE: To evaluate the concordance of identifying FH via SNOMED and ICD-10 CM codes vs the DLNC in an EHR database. METHODS: Using the Practice Fusion EHR database, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value were calculated comparing an FH cohort identified via SNOMED and ICD-10 CM codes to one identified via the DLNC. RESULTS: Among 907,616 patients with hypercholesterolemia, 2,180 were identified as FH via SNOMED code (zero were identified via ICD-10 CM), 259 had a DLNC score 6–8 (probable FH), and 45 had a DLNC score >8 (definite FH). Compared to DLNC score >8, the sensitivity, specificity, and PPV of the FH SNOMED code were 84.4%, 99.4%, and 6.4%, respectively. Compared to DLNC score ≥6, the sensitivity was 36.8% and the specificity was 99.5% with a PPV of 18.7%. CONCLUSION: Compared to the clinical criteria for FH, identification of FH patients via SNOMED diagnosis codes had high sensitivity and specificity, but low PPV. The discordance of these two techniques in identifying FH patients speaks to the challenges in identifying FH patients in large electronic databases such as administrative claims and EHR. |
format | Online Article Text |
id | pubmed-6241698 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-62416982018-12-07 How well can familial hypercholesterolemia be identified in an electronic health record database? Mues, Katherine E Bogdanov, Alina N Monda, Keri L Yedigarova, Larisa Liede, Alexander Kallenbach, Lee Clin Epidemiol Original Research BACKGROUND: Familial hypercholesterolemia (FH) is a condition characterized by high cholesterol levels and increased risk for coronary heart disease (CHD) that often goes undiagnosed. The Dutch Lipid Network Criteria (DLNC) are used to identify FH in clinical settings via physical examination, personal and family history of CHD, in addition to the presence of deleterious mutations of the LDLR, ApoB, and PCSK9 genes. Agreement between clinical and genetic diagnosis of FH varies. While an ICD diagnosis code was not available for coding FH until 2016, Systematized Nomenclature of Medicine (SNOMED) clinical concept codes, including genetic diagnoses, for FH have been utilized in electronic health records (EHRs). OBJECTIVE: To evaluate the concordance of identifying FH via SNOMED and ICD-10 CM codes vs the DLNC in an EHR database. METHODS: Using the Practice Fusion EHR database, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value were calculated comparing an FH cohort identified via SNOMED and ICD-10 CM codes to one identified via the DLNC. RESULTS: Among 907,616 patients with hypercholesterolemia, 2,180 were identified as FH via SNOMED code (zero were identified via ICD-10 CM), 259 had a DLNC score 6–8 (probable FH), and 45 had a DLNC score >8 (definite FH). Compared to DLNC score >8, the sensitivity, specificity, and PPV of the FH SNOMED code were 84.4%, 99.4%, and 6.4%, respectively. Compared to DLNC score ≥6, the sensitivity was 36.8% and the specificity was 99.5% with a PPV of 18.7%. CONCLUSION: Compared to the clinical criteria for FH, identification of FH patients via SNOMED diagnosis codes had high sensitivity and specificity, but low PPV. The discordance of these two techniques in identifying FH patients speaks to the challenges in identifying FH patients in large electronic databases such as administrative claims and EHR. Dove Medical Press 2018-11-15 /pmc/articles/PMC6241698/ /pubmed/30532597 http://dx.doi.org/10.2147/CLEP.S176853 Text en © 2018 Mues et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Original Research Mues, Katherine E Bogdanov, Alina N Monda, Keri L Yedigarova, Larisa Liede, Alexander Kallenbach, Lee How well can familial hypercholesterolemia be identified in an electronic health record database? |
title | How well can familial hypercholesterolemia be identified in an electronic health record database? |
title_full | How well can familial hypercholesterolemia be identified in an electronic health record database? |
title_fullStr | How well can familial hypercholesterolemia be identified in an electronic health record database? |
title_full_unstemmed | How well can familial hypercholesterolemia be identified in an electronic health record database? |
title_short | How well can familial hypercholesterolemia be identified in an electronic health record database? |
title_sort | how well can familial hypercholesterolemia be identified in an electronic health record database? |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6241698/ https://www.ncbi.nlm.nih.gov/pubmed/30532597 http://dx.doi.org/10.2147/CLEP.S176853 |
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