The Reach and Feasibility of an Interactive Lung Cancer Screening Decision Aid Delivered by Patient Portal

Ajay Dharod, Christina Bellinger, Kristie Foley, L Doug Case, David Miller, Ajay Dharod, Christina Bellinger, Kristie Foley, L Doug Case, David Miller

Abstract

Objective: Health systems could adopt population-level approaches to screening by identifying potential screening candidates from the electronic health record and reaching out to them via the patient portal. However, whether patients would read or act on sent information is unknown. We examined the feasibility of this digital health outreach strategy.

Methods: We conducted a single-arm pragmatic trial in a large academic health system. An electronic health record algorithm identified primary care patients who were potentially eligible for lung cancer screening (LCS). Identified patients were sent a patient portal invitation to visit a LCS interactive Web site which assessed screening eligibility and included a decision aid. The primary outcome was screening completion. Secondary outcomes included the proportion of patients who read the invitation, visited the interactive Web site, and completed the interactive Web site.

Results: We sent portal invitations to 1,000 patients. Almost all patients (86%, 862/1,000) read the invitation, 404 (40%) patients visited the interactive Web site, and 349 patients (35%) completed it. Of the 99 patients who were confirmed screening eligible by the Web site, 81 made a screening decision (30% wanted screening, 44% unsure, 26% declined screening), and 22 patients had a chest computed tomography completed.

Conclusion: The digital outreach strategy reached the majority of patient portal users. While the study focused on LCS, this digital outreach approach could be generalized to other health needs. Given the broad reach and potential low cost of this digital strategy, future research should investigate best practices for implementing the system.

Trial registration: ClinicalTrials.gov NCT02962115.

Conflict of interest statement

None declared.

Georg Thieme Verlag KG Stuttgart · New York.

Figures

Fig. 1
Fig. 1
Example screenshot of mPATH-Lung patient-reported information.
Fig. 2
Fig. 2
Example screenshot of mPATH-Lung personalized risk–benefit information.
Fig. 3
Fig. 3
Pragmatic trial flow diagram.
Fig. 4
Fig. 4
Time to event plot showing % of sample who read the message and % of sample who visited the Web app over time (from 0 to 120 days).

Source: PubMed

3
Abonneren