Cross sectional study to assess the accuracy of electronic health record data to identify patients in need of lung cancer screening

• Main Authors: Allison M. Cole, Bethann Pflugeisen, Malaika R. Schwartz, Sophie Cain Miller
• Format: Article
• Language: English
• Published: BMC 2018-01-01
• Series: BMC Research Notes
• Subjects: Electronic health records; Lung cancer; Cancer screening; Primary care
• Online Access: http://link.springer.com/article/10.1186/s13104-018-3124-0

Abstract 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.