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Identifying individuals with physician-diagnosed chronic obstructive pulmonary disease in primary care electronic medical records: a retrospective chart abstraction study

Little is known about using electronic medical records to identify patients with chronic obstructive pulmonary disease to improve quality of care. Our objective was to develop electronic medical record algorithms that can accurately identify patients with obstructive pulmonary disease. A retrospecti...

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Autores principales: Lee, Theresa M., Tu, Karen, Wing, Laura L., Gershon, Andrea S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5435091/
https://www.ncbi.nlm.nih.gov/pubmed/28507288
http://dx.doi.org/10.1038/s41533-017-0035-9
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author Lee, Theresa M.
Tu, Karen
Wing, Laura L.
Gershon, Andrea S.
author_facet Lee, Theresa M.
Tu, Karen
Wing, Laura L.
Gershon, Andrea S.
author_sort Lee, Theresa M.
collection PubMed
description Little is known about using electronic medical records to identify patients with chronic obstructive pulmonary disease to improve quality of care. Our objective was to develop electronic medical record algorithms that can accurately identify patients with obstructive pulmonary disease. A retrospective chart abstraction study was conducted on data from the Electronic Medical Record Administrative data Linked Database (EMRALD(®)) housed at the Institute for Clinical Evaluative Sciences. Abstracted charts provided the reference standard based on available physician-diagnoses, chronic obstructive pulmonary disease-specific medications, smoking history and pulmonary function testing. Chronic obstructive pulmonary disease electronic medical record algorithms using combinations of terminology in the cumulative patient profile (CPP; problem list/past medical history), physician billing codes (chronic bronchitis/emphysema/other chronic obstructive pulmonary disease), and prescriptions, were tested against the reference standard. Sensitivity, specificity, and positive/negative predictive values (PPV/NPV) were calculated. There were 364 patients with chronic obstructive pulmonary disease identified in a 5889 randomly sampled cohort aged ≥ 35 years (prevalence = 6.2%). The electronic medical record algorithm consisting of ≥ 3 physician billing codes for chronic obstructive pulmonary disease per year; documentation in the CPP; tiotropium prescription; or ipratropium (or its formulations) prescription and a chronic obstructive pulmonary disease billing code had sensitivity of 76.9% (95% CI:72.2–81.2), specificity of 99.7% (99.5–99.8), PPV of 93.6% (90.3–96.1), and NPV of 98.5% (98.1–98.8). Electronic medical record algorithms can accurately identify patients with chronic obstructive pulmonary disease in primary care records. They can be used to enable further studies in practice patterns and chronic obstructive pulmonary disease management in primary care.
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spelling pubmed-54350912017-05-19 Identifying individuals with physician-diagnosed chronic obstructive pulmonary disease in primary care electronic medical records: a retrospective chart abstraction study Lee, Theresa M. Tu, Karen Wing, Laura L. Gershon, Andrea S. NPJ Prim Care Respir Med Article Little is known about using electronic medical records to identify patients with chronic obstructive pulmonary disease to improve quality of care. Our objective was to develop electronic medical record algorithms that can accurately identify patients with obstructive pulmonary disease. A retrospective chart abstraction study was conducted on data from the Electronic Medical Record Administrative data Linked Database (EMRALD(®)) housed at the Institute for Clinical Evaluative Sciences. Abstracted charts provided the reference standard based on available physician-diagnoses, chronic obstructive pulmonary disease-specific medications, smoking history and pulmonary function testing. Chronic obstructive pulmonary disease electronic medical record algorithms using combinations of terminology in the cumulative patient profile (CPP; problem list/past medical history), physician billing codes (chronic bronchitis/emphysema/other chronic obstructive pulmonary disease), and prescriptions, were tested against the reference standard. Sensitivity, specificity, and positive/negative predictive values (PPV/NPV) were calculated. There were 364 patients with chronic obstructive pulmonary disease identified in a 5889 randomly sampled cohort aged ≥ 35 years (prevalence = 6.2%). The electronic medical record algorithm consisting of ≥ 3 physician billing codes for chronic obstructive pulmonary disease per year; documentation in the CPP; tiotropium prescription; or ipratropium (or its formulations) prescription and a chronic obstructive pulmonary disease billing code had sensitivity of 76.9% (95% CI:72.2–81.2), specificity of 99.7% (99.5–99.8), PPV of 93.6% (90.3–96.1), and NPV of 98.5% (98.1–98.8). Electronic medical record algorithms can accurately identify patients with chronic obstructive pulmonary disease in primary care records. They can be used to enable further studies in practice patterns and chronic obstructive pulmonary disease management in primary care. Nature Publishing Group UK 2017-05-15 /pmc/articles/PMC5435091/ /pubmed/28507288 http://dx.doi.org/10.1038/s41533-017-0035-9 Text en © The Author(s) 2017 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Lee, Theresa M.
Tu, Karen
Wing, Laura L.
Gershon, Andrea S.
Identifying individuals with physician-diagnosed chronic obstructive pulmonary disease in primary care electronic medical records: a retrospective chart abstraction study
title Identifying individuals with physician-diagnosed chronic obstructive pulmonary disease in primary care electronic medical records: a retrospective chart abstraction study
title_full Identifying individuals with physician-diagnosed chronic obstructive pulmonary disease in primary care electronic medical records: a retrospective chart abstraction study
title_fullStr Identifying individuals with physician-diagnosed chronic obstructive pulmonary disease in primary care electronic medical records: a retrospective chart abstraction study
title_full_unstemmed Identifying individuals with physician-diagnosed chronic obstructive pulmonary disease in primary care electronic medical records: a retrospective chart abstraction study
title_short Identifying individuals with physician-diagnosed chronic obstructive pulmonary disease in primary care electronic medical records: a retrospective chart abstraction study
title_sort identifying individuals with physician-diagnosed chronic obstructive pulmonary disease in primary care electronic medical records: a retrospective chart abstraction study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5435091/
https://www.ncbi.nlm.nih.gov/pubmed/28507288
http://dx.doi.org/10.1038/s41533-017-0035-9
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