Insights from the Nationwide TriNetX Dataset Comparing Time-to Follow-up, Staging, and Referral Post-CT Lung Cancer Diagnosis

The study problem addresses health disparities in African American males related to timeliness of post-diagnosis lung cancer care, including follow-up appointment, staging, and referral for treatment. Although advances in diagnostic imaging have improved early detection, significant inequities persist in the period following a confirmed diagnosis, where delays in care can lead to disease progression and poor survival outcomes. The theoretical framework is the Health Belief Model (HBM) which explains health behavior through perceptions of susceptibility, severity, benefits, and barriers to action. The overall study aim is to quantify the differences in average time to first follow-up appointment, staging, and referral post CT-diagnosed lung cancer between African American males and White males. The global research question is: What are the differences in average time to first follow-up appointment, staging, and referral following a CT-based lung cancer diagnosis between African American males and White males? The null hypothesis is: There are no difference in average time to first follow-up appointment, staging, or referral following a CT-based lung cancer diagnosis between African American males and White males. The significance of the study lies in its focus on a population that experiences the highest lung cancer mortality yet remains underrepresented in post-diagnosis research. By examining care after diagnosis rather than screening participation, this study addresses a critical gap in the literature and contributes to evidence-based strategies for improving equity in care coordination, timeliness, and treatment initiation among African American males. The study design is a retrospective secondary analysis using electronic medical record data from the TriNetX Database comparing average time to first follow-up appointment, staging, and referral post CT-based lung cancer diagnosis between African American males and White males. The design is justified because secondary analysis allows the leveraging of existing datasets to efficiently examine disparities in care delivery without the time and resource constraints of primary data collection.

Name thesis:degree_name

PhD in Nursing (Doctoral)

Grantor

The University of Texas Medical Branch at Galveston

Year dc:date.issued

2025

Author dc:creator

• McGaskey, Angela

Committee members dc:contributor.committeemember

• Hickerson, Latia (lwhicker@utmb.edu)
• Kuo, Yong-Fang (yokuo@utmb.edu)
• Forbes, Sheryl (slguiney@mdanderson.org)

Language dc:language.iso

English

Handle dc:identifier.uri

https://hdl.handle.net/2152.3/12814

OAI identifier oai:identifier

oai:utmb-ir.tdl.org:2152.3/12814