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Published on: July 28, 2022
Real-world evaluation of user engagement with an artificial intelligence-powered clinical trial application in
Tony K W Hung1,2, Jun J Mao3, Alan L Ho3
1Cancer Institute, Hartford HealthCare, Hartford, CT 06106, United States.
Objectives:
This quality improvement study implemented and prospectively examined user engagement with an artificial intelligence (AI)-powered clinical trial knowledge management application at an NCI-designated comprehensive cancer center.
Materials And Methods:
We prospectively auto-captured user engagement measures from July 1, 2022 to February 29, 2024. Measurement included: (1) event: an app interaction; (2) session: group of events within single setting; (3) engaged session: session longer than 10 s; (4) engagement time; (5) app downloads; (6) active user; and (7) stickiness: monthly active users per normalized total downloads. We analyzed the measures using time series and linear regression.
Results:
During a 20-month evaluation, the application supported 138 clinical trials, recorded 136 632 user interactions, including 2754 engaged sessions with an average engagement time of 6 min 31 s. Of 243 downloads, 228 (94%) users remained active, with an estimated stickiness score of 3.12 (SD 0.91), indicating sustained provider engagement.
Discussion:
This study provided insights into the feasibility and potential for integrating an AI-powered clinical trial knowledge management application into oncology workflows, with sustained engagement among providers over a 20-month period. High rates of active users and session stickiness suggest that such application offered meaningful utility in real-world clinical settings, underscoring the need for future studies to assess optimal integration strategies and impact on clinical trial accrual.
Conclusion:
This study addresses an important gap in the literature regarding the real-world integration of AI technologies in oncology care and offers valuable insights for future research and clinical practice.
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