ABSTRACT
Since December 2013, the U.S. Preventive Services Task Force has recommended lung cancer screening
(LCS) with low-dose computed tomography for high-risk individuals with a smoking history, affording a major
opportunity to reduce lung cancer mortality, especially in racial/ethnic and disadvantaged populations that are
disproportionately affected by the disease. Yet, there is concern that LCS is not being delivered effectively and
equitably, given its many unique implementation challenges. LCS utilization remains low. Emerging data also
suggest poorer uptake of LCS in Black versus white individuals. Even less is known about racial/ethnic
disparities in smoking cessation, although smoking cessation counseling is an integral component of the LCS
process. Identifying factors associated with LCS utilization, particularly those that contribute to racial/ethnic
disparities, is thus critical to deliver LCS optimally. Following well-established conceptual frameworks in which
multiple levels of influence affect cancer screening behaviors, we posit that LCS utilization is affected by
individual-, neighborhood-, provider-, and health facility-level factors. Studies to identify multilevel factors
associated with LCS utilization have been limited to date, due in part to known constraints in the data sources
available to evaluate LCS, especially at steps before screening initiation. Electronic health records (EHR) are a
recognized but largely untapped data source to address LCS. Compared to other data sources, integrated
health system EHRs capture comprehensive longitudinal data on clinical services from a defined population,
providing a robust and efficient means to investigate multilevel determinants of disparities in LCS utilization. In
our foundational work using EHR data to characterize early patterns of LCS utilization, we found evidence of
racial/ethnic disparities in the process after screening initiation. In this proposal, we aim to identify and
understand multilevel determinants of racial/ethnic disparities in LCS utilization, before and up through
screening initiation. Specifically, we will determine the influence of factors at the individual, neighborhood,
provider, and facility levels on disparities in LCS utilization, starting from the opportunity to be screened, as
measured by the completeness of EHR documentation on smoking history to assess LCS eligibility (Aim 1),
followed by LCS referral and initiation (Aim 2) and referral and use of smoking cessation services (Aim 3). We
will compile, link, and analyze available EHR, questionnaire, and geospatial data from a sociodemographically
diverse population of over 1.3 million adults in an integrated health system from 2014 to 2023. Overall, our
multilevel analysis will generate valuable insight into the major and modifiable drivers of racial/ethnic disparities
at key steps in LCS from eligibility assessment to screening initiation. These findings will provide an empirical
basis to guide health systems in developing multilevel interventions that improve LCS outreach and utilization,
both effectively and equitably.