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Cross sectional study to assess the accuracy of electronic health record data to identify patients in need of lung cancer screening
OBJECTIVE: Lung cancer is the leading cause of cancer death in the United States [Siegel et al. in CA Cancer J Clin 66:7–30, 1]. However, evidence from clinical trials indicates that annual low-dose computed tomography screening reduces lung cancer mortality [Humphrey et al. in Ann Intern Med 159:41...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5763525/ https://www.ncbi.nlm.nih.gov/pubmed/29321038 http://dx.doi.org/10.1186/s13104-018-3124-0 |
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author | Cole, Allison M. Pflugeisen, Bethann Schwartz, Malaika R. Miller, Sophie Cain |
author_facet | Cole, Allison M. Pflugeisen, Bethann Schwartz, Malaika R. Miller, Sophie Cain |
author_sort | Cole, Allison M. |
collection | PubMed |
description | OBJECTIVE: Lung cancer is the leading cause of cancer death in the United States [Siegel et al. in CA Cancer J Clin 66:7–30, 1]. However, evidence from clinical trials indicates that annual low-dose computed tomography screening reduces lung cancer mortality [Humphrey et al. in Ann Intern Med 159:411–420, 2]. The objective of this study is to report results of a study designed to assess the sensitivity, specificity, and positive and negative predictive value of an electronic health record (EHR) query in comparison to patient self-report, to identify patients who may benefit from lung cancer screening. Cross sectional study comparing patient self report to EHR derived assessment of tobacco status and need for lung cancer screening. We invited 200 current or former smokers, ages 55–80 to complete a brief paper survey. 26 responded and 24 were included in the analysis. RESULTS: For 30% of respondents, there was not adequate EHR data to make a lung cancer screening determination. Compared to patient self-report, EHR derived data has a 67% sensitivity and 82% specificity for identifying patients that meet criteria for lung cancer screening. While the degree of accuracy may be insufficient to make a final lung cancer screening determination, EHR data may be useful in prompting clinicians to initiate conversations with patients in regards to lung cancer screening. |
format | Online Article Text |
id | pubmed-5763525 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57635252018-01-17 Cross sectional study to assess the accuracy of electronic health record data to identify patients in need of lung cancer screening Cole, Allison M. Pflugeisen, Bethann Schwartz, Malaika R. Miller, Sophie Cain BMC Res Notes Research Note OBJECTIVE: Lung cancer is the leading cause of cancer death in the United States [Siegel et al. in CA Cancer J Clin 66:7–30, 1]. However, evidence from clinical trials indicates that annual low-dose computed tomography screening reduces lung cancer mortality [Humphrey et al. in Ann Intern Med 159:411–420, 2]. The objective of this study is to report results of a study designed to assess the sensitivity, specificity, and positive and negative predictive value of an electronic health record (EHR) query in comparison to patient self-report, to identify patients who may benefit from lung cancer screening. Cross sectional study comparing patient self report to EHR derived assessment of tobacco status and need for lung cancer screening. We invited 200 current or former smokers, ages 55–80 to complete a brief paper survey. 26 responded and 24 were included in the analysis. RESULTS: For 30% of respondents, there was not adequate EHR data to make a lung cancer screening determination. Compared to patient self-report, EHR derived data has a 67% sensitivity and 82% specificity for identifying patients that meet criteria for lung cancer screening. While the degree of accuracy may be insufficient to make a final lung cancer screening determination, EHR data may be useful in prompting clinicians to initiate conversations with patients in regards to lung cancer screening. BioMed Central 2018-01-10 /pmc/articles/PMC5763525/ /pubmed/29321038 http://dx.doi.org/10.1186/s13104-018-3124-0 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Note Cole, Allison M. Pflugeisen, Bethann Schwartz, Malaika R. Miller, Sophie Cain Cross sectional study to assess the accuracy of electronic health record data to identify patients in need of lung cancer screening |
title | Cross sectional study to assess the accuracy of electronic health record data to identify patients in need of lung cancer screening |
title_full | Cross sectional study to assess the accuracy of electronic health record data to identify patients in need of lung cancer screening |
title_fullStr | Cross sectional study to assess the accuracy of electronic health record data to identify patients in need of lung cancer screening |
title_full_unstemmed | Cross sectional study to assess the accuracy of electronic health record data to identify patients in need of lung cancer screening |
title_short | Cross sectional study to assess the accuracy of electronic health record data to identify patients in need of lung cancer screening |
title_sort | cross sectional study to assess the accuracy of electronic health record data to identify patients in need of lung cancer screening |
topic | Research Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5763525/ https://www.ncbi.nlm.nih.gov/pubmed/29321038 http://dx.doi.org/10.1186/s13104-018-3124-0 |
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