A Quantitative Analysis of Patient-Facing Technologies for Patient Self-Reporting.

Dramatic improvements in patient-facing technologies have demonstrated the potential to transform healthcare delivery for a 360-degree holistic view of care. A key question regarding how such technologies affect patient self-reporting still needs to be answered. This study presents the technologies and their associated key variables via quantitative analysis. Associations were found between single-platform and web-based applications (apps), Android apps and physician view, mental health disease, and user feedback. The results are intended to inform future design, development, and evaluation of patient-facing technologies. More systematic, theory-driven, framework-based design and evaluation are necessary to fully characterize the effectiveness and maintenance of patient-facing technologies toward a sustainable strategy.

Exploring a Mechanism Toward Automated Feedback for Cancer Patient Self-Reporting.

"Infobuttons" spearheaded electronic health records (EHR) based decision support by offering automated knowledge resources to physicians. However, how such a mechanism could be leveraged to provide optimal resources to patients remains unanswered. Informatics approaches are expected to utilize more relevant information beyond EHR, such as patient-reported outcomes, to support clinical decisions. This pilot study is intended to explore how patient-reported outcomes version of the common terminology criteria for adverse events (PRO-CTCAE) in EHR can be incorporated and how to recommend tailored content to cancer patients via automated feedback.