Proactive, Prediction-Driven Outreach for Lung Cancer Screening: Development and Feasibility of a Population...

Area of Science:

• Public Health
• Health Services Research
• Oncology

Background:

• Lung cancer screening (LCS) uptake remains suboptimal, failing to reach many patients who would benefit most.
• Effective strategies are needed to proactively identify and engage high-benefit individuals in LCS programs.

Purpose of the Study:

• To develop and pilot test a prediction-driven population management approach for proactive identification and engagement of high-benefit patients in LCS.
• To assess the feasibility and acceptability of this approach among clinicians and patients.

Main Methods:

• A four-phase feasibility study involving formative interviews, toolkit development, pilot testing, and postpilot interviews.
• Development of a population management toolkit with a dashboard displaying LCS-eligible patients ranked by predicted benefit.
• User-centered design informed by interviews with 38 clinicians and patients, followed by pilot testing at five LCS sites.

Main Results:

• Clinicians and patients positively endorsed proactive LCS population management and outreach.
• Clinicians valued expert engagement of high-benefit patients and reduced primary care strain.
• Patients preferred clear, nonstigmatizing, team-based outreach via letters and phone calls, influencing toolkit refinement.

Conclusions:

• A prediction-driven population management and proactive outreach strategy for LCS is feasible and acceptable.
• Further research is warranted to evaluate the impact of this approach on LCS uptake and patient outcomes.