Kris F. Wain, PhD
Investigator
Kris F. Wain, PhD, is an Investigator and Health Economist at the Institute for Health Research. Dr. Wain’s research focuses on health outcomes and healthcare costs across the cancer care continuum. He also evaluates and implements innovative healthcare models aimed at improving access to care, increasing use of high-value and preventive services, and improving health outcomes.
Dr. Wain earned his Master of Science degree in Health Economics from the University of Colorado Denver and completed his doctoral training in Health Economics at the Colorado School of Public Health . He is the principal investigator of a National Cancer Institute (NCI) funded study examining barriers to lung cancer screening and recently led an intervention to “nudge” patients toward cancer screening that has been incorporated into standard care at Kaiser Permanente Colorado. He has also worked extensively with the NCI-funded Lung PROSPR Research Center (Lung-PRC) to improve lung cancer screening.
Selected Research:
- Examining Barriers to Lung Cancer Screening
- Funder: National Institutes of Health/National Cancer Institute
- Study End Date: 12/31/2026
- Using Large Language Models to Extract Quantitative Smoking Data from Unstructured Clinical Progress Notes
- Funder: Strategic, Targeted, Allocation of Resources (STAR)
- Study End Date: 12/31/2026
- Promoting Lung Cancer Screening Participation with a Video Nudge
- Funder: Innovative Methods to Promote Regional Operational Value and Efficiency (IMPROVE)
- Study End Date: 12/31/2025
- Lung PROSPR Research Center (Lung-PRC)
- Funder: National Institutes of Health/National Cancer Institute
- Award End Date: 07/31/2025
Barriers to lung cancer screening participation are poorly understood, creating challenges in identifying and intervening for individuals at elevated risk of not receiving screening. Findings from this study can equip healthcare systems with actionable evidence to conduct outreach efforts and implement cost-effective interventions aimed at enhancing LCS participation and adherence, while reducing screening disparities.
Despite clinical guidelines recommending routine assessment of smoking history during each patient’s encounter, smoking data are often incomplete, inaccurate, and recorded in unstructured sections of the electronic health record, thus many individuals at highest risk for lung cancer are neither identified nor engaged for lung cancer screening. The primary objective of this study is to develop and evaluate a large language model tool to extract quantitative smoking history data, including smoking status, pack-years, and years since quit from unstructured clinical progress notes. Building on our prior successful use of LLMs, we will deploy an LLM infrastructure and develop a targeted prompt to extract smoking history data from unstructured progress notes and assess whether LLM-derived data provides incremental improvement over existing LCS eligibility prediction algorithms.
The U.S. Preventive Services Task Force requires shared decision-making between patients and providers prior to undergoing screening to ensure an informed discussion of the benefits and risks. However, many patients do not participate in shared decision-making, often due to patient- and provider-level barriers such as financial concerns and limited time. This intervention leverages principles from “nudge” theory to enhance patient engagement in the shared decision-making process and increase participation in KPCO’s LCS program by addressing barriers at both the patient and provider levels.
This project focuses on evaluating the benefits, harms, and costs of lung cancer screening and prevention in community health systems, with a particular focus on improving lung cancer screening and addressing health disparities in lung cancer-related deaths.