Patients are capable of reporting symptoms experienced during chemotherapy using a Web-based interface. Assessment in the clinical trial setting and comparison of direct patient- versus clinician-based approaches for reporting symptoms and their severity are warranted.

Online patient self-reporting is a feasible long-term strategy for toxicity symptom monitoring during chemotherapy, even among patients with advanced cancer and high symptom burdens. However, without explicit reminders and clinician feedback, patients demonstrated limited voluntary interest in self-reporting between visits.

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The current mechanism for monitoring toxicity symptoms in cancer trials depends on a complex paper-based process. Electronic collection of patient-reported outcomes (PROs) may be more efficient and accurate. An online PRO platform was created including a simple data entry interface, real-time report generation, and an alert system to e-mail clinicians when patients self-report serious toxicities. Feasibility assessment involving 180 chemotherapy patients demonstrated high levels of use at up to 40 follow-up clinic visits per patient over 16 months (85% of patients at any given visit), with high levels of patient and clinician acceptance and satisfaction (>95%). Alerts were used as the basis for delayed chemotherapy treatments, dose modifications, and scheduling changes. These results demonstrate that online patient-reporting is a feasible strategy for chemotherapy toxicity symptom monitoring, and may improve safety and satisfaction with care. Ongoing multi-center research will evaluate the impact of this approach on clinical and administrative outcomes.

Using a variety of techniques including Topic Modeling, Principal Component Analysis and Bi-clustering, we explore electronic patient records in the form of unstructured clinical notes and genetic mutation test results. Our ultimate goal is to gain insight into a unique body of clinical data, specifically regarding the topics discussed within the note content and relationships between patient clinical notes and their underlying genetics.