Multilevel Determinants of Differences in Lung Cancer Screening Utilization

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. Yet, there is concern that LCS is not being delivered effectively, given its many unique implementation challenges. LCS utilization remains low to date. Even less is known about the impact of LCS on smoking cessation, although smoking cessation counseling is an integral component of the LCS process. Identifying factors associated with LCS utilization 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 differences in LCS utilization. In our foundational work using EHR data to characterize early patterns of LCS utilization, we found evidence of individual-level differences in the process after screening initiation. In this proposal, we aim to identify and understand multilevel determinants of differences 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 differences 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 representative 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 differences 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.