OBJECTIVES: Approximately 1.8 million individuals worldwide succumb to lung cancer annually, making it the primary cause of cancer-related mortality. The introduction of low-dose CT scans as part of screening programs has led to an increase in the number of patients with treatable early-stage lung cancer. However, biopsies and surgeries for small nodules can be particularly complex in terms of localization and accessibility. The purpose of this study was to examine the budget impact of adopting a more precise and minimally invasive method, a Lung Suite platform, a real-time 3D imaging navigation platform, to diagnose and immediately treat lung cancer patients using procedures like tumour ablation in a single room.

METHODS: A budget impact model was developed comparing the conventional lung cancer diagnosis and treatment patient pathway to the Lung Suite navigation platform from a US hospital perspective. Diagnostic yields, incidence rates, and complication rates were obtained from literature and real-world data: the Medicare Limited Datasets 5% Sample, Optum Clinformatics Data Mart, Premier Hospital Database, and Definitive Healthcare. Hospital costs and reimbursements were also obtained from these databases. Billing codes were used to identify outpatient and inpatient procedures. Weighted averages were used to represent public and private payer reimbursements and costs for each procedure.

RESULTS: Offsetting the cost of the Lung Suite navigation platform is dependent on the timeframe and epidemiological factors. In the case of 250 patients, cost savings of close to $2 million and contribution margin of over $125,000 are realised for a US hospital within a 2-year period due to a higher diagnostic yield and streamlined treatment pathway.

CONCLUSIONS: Hospitals adopting the Lung Suite navigation platform can realize cost savings and better contribution margins over time versus the conventional pathway, while also delivering better patient outcomes and efficiencies to the patient pathway.