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Published on: August 1, 2019
Electronic Health Record Prompt to Improve Lung Cancer Screening in Primary Care
Michael B Steinberg1, William J Young2, Erin J Miller Lo2
1The Department of Medicine, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, New Jersey; Rutgers Center for Tobacco Studies, Rutgers, The State University of New Jersey, New Brunswick, New Jersey.
Introduction:
Lung cancer is the leading cause of cancer death in the U.S. Combusted tobacco use, the primary risk factor, accounts for 90% of all lung cancers. Early detection of lung cancer improves survival, yet lung cancer screening rates are much lower than those of other cancer screening tests. Electronic health record (EHR) systems are an underutilized tool that could improve screening rates.
Methods:
This study was conducted in the Rutgers Robert Wood Johnson Medical Group, a university-affiliated network in New Brunswick, NJ. Two novel EHR workflow prompts were implemented on July 1, 2018. These prompts included fields to determine tobacco use and lung cancer screening eligibility and facilitated low-dose computed tomography ordering for eligible patients. The prompts were designed to improve tobacco use data entry, allowing for better lung cancer screening eligibility identification. Data were analyzed in 2022 retrospectively for the period July 1, 2017 to June 30, 2019. The analyses represented 48,704 total patient visits.
Results:
The adjusted odds of patient record completeness to determine eligibility for low-dose computed tomography (AOR=1.19, 95% CI=1.15, 1.23), eligibility for low-dose computed tomography (AOR=1.59, 95% CI=1.38, 1.82), and whether low-dose computed tomography was ordered (AOR=1.04, 95% CI=1.01, 1.07) all significantly increased after the electronic medical record prompts were implemented.
Conclusions:
These findings show the utility and benefit of EHR prompts in primary care settings to increase identification for lung cancer screening eligibility as well as increased low-dose computed tomography ordering.
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