A Patient-Centered Model of Fast-Track Lung Cancer Diagnosis

Despite the increasing importance of digital resources in modern life over the past decades, little is known about the impact of internet-based solutions on patient's health. We aimed to study the potential benefit of a digital platform helping patients to deal with abnormal chest CT scan revealing possible lung cancer.

We set up a fast-track lung cancer diagnosis pathway through a secure online platform. Patient-generated information combined with online review of their imaging enables preplanning of further investigations ahead of clinical assessment. We compared outcomes of "self-referred" patients (patient group), who directly fill out the online questionnaire, to general practitioner-driven patients (GP group), who were referred by their GP.

From June 2021 to June 2022, we included 125 patients (61% males, median age 67 years, IQR 56.9-72.5): 41% in the patient group and 59% in the GP group. No difference was found between groups in terms of time from contact to first appointment (median 5 days in both groups, P = .6), percentage of pathways including prebooked tests (94% vs. 92%, P = .6), number of scheduled invasive procedures (median 1, IQR 1-2 vs. 2, IQR 1-2, P = .4) and in final cancer diagnosis (76% vs. 78%, P = .4).

A lung cancer diagnosis pathway directly accessible by patients through a secure online platform was feasible and as efficient as the usual general practitioner pathway. It demonstrated the benefit of leaning on new digital tools in order to answer to the new challenges of a patient-centered health care system.