Breast Cancer Screening in Rural West Texas: Access Barriers, Follow-Up Fragmentation, and AI-Enabled Oncology Care Delivery.
Authors
Affiliations (4)
Affiliations (4)
- Department of Internal Medicine, Division of Hematology and Medical Oncology, Texas Tech University Health Sciences Center, Lubbock, TX, USA.
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA.
- Department of Radiology, Division of Breast Imaging, University Medical Center, Lubbock, TX, USA.
- Department of Surgery, Division of Breast Surgery, Texas Tech University Health Sciences Center, Lubbock, TX, USA.
Abstract
Breast cancer screening can reduce mortality, but its benefit depends on timely diagnostic resolution and access to treatment. This narrative review examines screening in rural West Texas as an oncology care-delivery continuum, integrating evidence on geographic and financial barriers, abnormal-result follow-up, navigation, regional screening programs, and artificial intelligence (AI). Mobile mammography and community outreach can improve initial access; their effectiveness depends on diagnostic capacity, clear referral responsibilities, accessible communication, and tracking through resolution. Regional evidence supports attention to structural barriers and workforce distribution, although breast-specific capacity data remain limited. A proposed regional framework links outreach and mammography with navigation, diagnostic imaging, biopsy, multidisciplinary referral, and treatment initiation. AI-assisted image interpretation, risk prediction, and follow-up coordination are distinct applications with different evidence and workload implications. Evidence from organized screening programs supports selected imaging applications, but does not establish a reduction in total clinical workload or improved diagnostic completion in rural West Texas. AI should therefore be considered an optional, locally evaluated adjunct after the pathway needed to act on its outputs is established. Program assessment should extend beyond mammography volume to diagnostic completion, time to treatment, workload, and equity.