PCN275 BENEFITS AND CHALLENGES OF MOBILE HEALTH APPLICATIONS IN PROSPECTIVE STUDIES: LEARNINGS FROM THE MADELINE STUDY AND LITERATURE

Abstract

To evaluate benefits and challenges when implementing a novel mobile application (“app”) within a prospective site-based multicenter study. A targeted literature review was conducted, and experience was collected from the MADELINE study, a United States study of patients with HR+/HER2- advanced/metastatic breast cancer (aBC/mBC) initiating palbociclib combination therapy or other approved therapies for aBC/mBC that employed a novel mobile application for capture of patient responses to requested daily, weekly, and monthly or cycle-based surveys on symptoms and quality of life for up to 6 months. Eligible patients needed to have access to a smartphone compatible with the application. The literature review identified important elements in the design and implementation of mobile apps for use in a prospective study including more traditional themes such as fostering collaborative relationships between the technical and research teams, extensive testing of the app, and review of test data to ensure that the data are of sufficient quality and acceptable format. Other themes specific to mobile Health (mHealth) applications such as understanding how updates work and the necessity of rollout campaigns to encourage patient compliance were also identified. Although mHealth applications allow for the collection of large amounts of data, analysis and summarization can be complicated, particularly in handling missing data. Pragmatic challenges with MADELINE highlight complexities of the data collected. In our study the mobile app was designed to allow collection of patient data at the same time in a treatment cycle regardless of the length of the cycle—a clear benefit in oncology studies. However, the analysis algorithm was complicated and required extensive derivation outside of the app due to missing data. While mHealth provides great opportunity, the benefit and challenges unique to mHealth should be understood in the specific context being studied to ensure data quality and analytic capability.