OBJECTIVES: We describe the development and implementation of a system for monitoring patient-reported adverse events and quality of life using electronic Patient Reported Outcome (ePRO) instruments in the I-SPY2 Trial, a phase II clinical trial for locally advanced breast cancer. We describe the administration of technological, workflow, and behavior change interventions and their associated impact on questionnaire completion. MATERIALS AND METHODS: Using the OpenClinica electronic data capture system, we developed rules-based logic to build automated ePRO surveys, customized to the I-SPY2 treatment schedule. We piloted ePROs at the University of California, San Francisco (UCSF) to optimize workflow in the context of trial treatment scenarios and staggered rollout of the ePRO system to 26 sites to ensure effective implementation of the technology. RESULTS: Increasing ePRO completion requires workflow solutions and research staff engagement. Over two years, we increased baseline survey completion from 25% to 80%. The majority of patients completed between 30% and 75% of the questionnaires they received, with no statistically significant variation in survey completion by age, race or ethnicity. Patients who completed the screening timepoint questionnaire were significantly more likely to complete more of the surveys they received at later timepoints (mean completion of 74.1% vs 35.5%, P < .0001). Baseline PROMIS social functioning and grade 2 or more PRO-CTCAE interference of Abdominal Pain, Decreased Appetite, Dizziness and Shortness of Breath was associated with lower survey completion rates. DISCUSSION AND CONCLUSION: By implementing ePROs, we have the potential to increase efficiency and accuracy of patient-reported clinical trial data collection, while improving quality of care, patient safety, and health outcomes. Our method is accessible across demographics and facilitates an ease of data collection and sharing across nationwide sites. We identify predictors of decreased completion that can optimize resource allocation by better targeting efforts such as in-person outreach, staff engagement, a robust technical workflow, and increased monitoring to improve overall completion rates. TRIAL REGISTRATION: https://clinicaltrials.gov/study/NCT01042379.

OBJECTIVE: Develop and evaluate a foundational oncology-specific standard for the communication and coordination of care throughout the cancer journey, with early-stage breast cancer as the use case. MATERIALS AND METHODS: Owing to broad uptake of the Health Level Seven (HL7) Consolidated Clinical Document Architecture (C-CDA) by health information exchanges and large provider organizations, we developed an implementation guide in congruence with C-CDA. The resultant product was balloted through the HL7 process and subsequently implemented by two groups: the Health Story Project (Health Story) and the Athena Breast Health Network (Athena). RESULTS: The HL7 Implementation Guide for CDA, Release 2: Clinical Oncology Treatment Plan and Summary, DSTU Release 1 (eCOTPS) was successfully balloted and published as a Draft Standard for Trial Use (DSTU) in October 2013. Health Story successfully implemented the eCOTPS the 2014 meeting of the Healthcare Information and Management Systems Society (HIMSS) in a clinical vignette. During the evaluation and implementation of eCOPS, Athena identified two practical concerns: (1) the need for additional CDA templates specific to their use case; (2) the many-to-many mapping of Athena-defined data elements to eCOTPS. DISCUSSION: Early implementation of eCOTPS has demonstrated successful vendor-agnostic transmission of oncology-specific data. The modularity enabled by the C-CDA framework ensures the relatively straightforward expansion of the eCOTPS to include other cancer subtypes. Lessons learned during the process will strengthen future versions of the standard. CONCLUSION: eCOTPS is the first oncology-specific CDA standard to achieve HL7 DSTU status. Oncology standards will improve care throughout the cancer journey by allowing the efficient transmission of reliable, meaningful, and current clinical data between the many involved stakeholders.

Informatics in biomedicine is becoming increasingly interconnected via distributed information services, interdisciplinary correlation, and crossinstitutional collaboration. Partnering with NASA, the Early Detection Research Network (EDRN), a program managed by the National Cancer Institute, has been defining and building an informatics architecture to support the discovery of biomarkers in their earliest stages. The architecture established by EDRN serves as a blueprint for constructing a set of services focused on the capture, processing, management and distribution of information through the phases of biomarker discovery and validation.

MOTIVATION: Microarrays are an important research tool for the advancement of basic biological sciences. However this technology has yet to be integrated with clinical decision making. We have implemented an information framework based on the Microarray Gene Expression Markup Language (MAGE-ML) specification. We are using this framework to develop a test-bed integrated database application to identify genomic and imaging markers for diagnosis of breast cancer. RESULTS: We developed extensible software architecture for retrieving data from different microarray databases using MAGE-ML and for combining microarray data with breast cancer image analysis and clinical data for correlation studies. The framework we developed will provide the necessary data integration to move microarray research from basic biological sciences to clinical applications. AVAILABILITY: Open source software will be available from SourceForge (http://sourceforge.net/projects/microsoap/).