To understand participants' barriers to lung cancer screening and their experience with scheduling lung cancer screening.
Primary Objectives/Aims 1. Determine rates of lung cancer scheduling and screening at the UTMB and UT Tyler LCS programs. 2. Using state-of-the-art machine learning (ML) approaches, develop prediction models for adherence to screening guidelines for newly eligible and established patients. Investigators will leverage data from BRFSS, UT Tyler and UTMB to develop and validate the prediction model, ensuring its generalizability and accuracy. 3. Survey participants in the LCS programs about their impressions and experience with the scheduling and completing screening; conduct interviews with participants who receive an order for LCS but do not complete screening by their due date. 4. Interview LCS program directors and staff about barriers and facilitators of increasing screening rates in their programs.
Study Type
OBSERVATIONAL
Enrollment
340
Participants who agree to take part in this study, will participate in an interview. During the interview, participants may be asked about: • Participants background information, such as your race and level of education • Participants lung cancer diagnosis and your history of lung cancer screening • Participants experience with scheduling lung cancer screening • Any barriers that kept participants from completing screening
MD Anderson Cancer Center
Houston, Texas, United States
RECRUITINGSafety and Adverse Events (AEs)
Time frame: Through study completion; an average of 1 year.
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