Developing a systems-focused tool for modeling lung cancer screening resource needs

Abstract

Background: Early detection through screening dramatically improves lung cancer survival rates, including among war Veterans, who are at heightened risk. The effectiveness of low dose computed tomography scans in lung cancer screening (LCS) prompted the Veteran's Affairs Lung Precision Oncology Program (VA LPOP) to increase screening rates. We aimed to develop an adaptive population health tool to determine adequate resource allocation for the program, with a specific focus on primary care providers, nurse navigators, and radiologists.

Methods: We developed a tool using C + + that uses inputs that represents the process of the VA LCS program in Ann Arbor, Michigan to calculate FTEs of human resource needs to screen a given population. Further, we performed a sensitivity analysis to understand how resource needs are impacted by changes in population, screening eligibility, and time allocated for the nurse navigators' tasks.

Results: Using estimates from the VA LCS Program as demonstrative inputs, we determined that the greatest number of full-time equivalents required were for radiologists, followed by nurse navigators and then primary care providers, for a target population of 75,000. An increase in the population resulted in a linear increase of resource needs, with radiologists experiencing the greatest rate of increase, followed by nurse navigators and primary care providers. These resource requirements changed with primary care providers, nurse navigators and radiologists demonstrating the greatest increase when 1-20, 20-40 and > 40% of Veterans accepted to be screened respectively. Finally, when increasing the time allocated to check eligibility by the nurse navigator from zero to three minutes, there was a linear increase in the full-time equivalents required for the nurse navigator.

Conclusion: Variation of resource utilization demonstrated by our user facing tool emphasizes the importance of tailored strategies to accommodate specific population demographics and downstream work. We will continue to refine this tool by incorporating additional variability in system parameters, resource requirements following an abnormal test result, and resource distribution over time to reach steady state. While our tool is designed for a specific program in one center, it has wider applicability to other cancer screening programs.

Keywords: Interventions; Lung cancer screening program; Resource allocations; Screening; Veterans affairs.

Fig. 1

Process Map for Demonstrative Example: Lung Cancer Screening Program, VA Ann Arbor demonstrates the steps involved in lung cancer screening and key human resources involved including Nurse Navigators (NNs), primary care providers (PCPs), and radiologists, who aid in subdividing the population into subgroups by criteria until every patient in the population completes one cycle of screening in the program

Fig. 2

Resource Requirements for NN, Radiologist and PCP in FTEs. The number of FTEs required for each resource type based on the inputs used in Table 1

Fig. 3

a: Resource Requirements for NN, Radiologist and PCP with an Increasing VA Population. b: Resource Requirements for NN, Radiologist and PCP with Varying Percent of Eligible Veterans. c: Resource Requirements for NN with Varying Task Duration to Discuss Screening. Sensitivity analysis following varying initial eligibility and task duration: a depicts the impact on Full Time Equivalents (FTEs) for each resource type when the initial population increases, holding all other parameters from Table 1 constant. b depicts the impact on Full time Equivalents (FTEs) when the percentage of eligible Veterans who agreed to be screened changes, holding the population constant at 75,000. c depicts the impact on Full Time Equivalents (FTEs) when the duration of the task to discuss screening changes with a fixed population of 75,000 and holding all other parameters from Table 1