Medidata Rave® Data Capture & Management
NCI has designated Medidata Rave as its recommended electronic data collection system for CP-CTNet to improve the consistency of data collection across a large number of institutions and trials. Medidata Rave is an electronic data capture (EDC) and clinical data management (CDM) platform for capturing, managing and reporting of clinical, operational and safety data within a single system. Rave enables users to efficiently and effectively map study-related processes and user responsibilities for recording patient information (i.e., visit, lab, and adverse event data) using common data elements (CDEs) forms that are customized for each study.
Data Integration Program
The Data Integration Program maintains a system for collecting and reporting a subset of clinical trial data to NCI and DCP via the monthly Minimum Data Set (MDS) report. The MDS is a data reporting mechanism which allows submitters to report a defined subset of study data to NCI DCP. This subset of data is obtained from the study’s database of record and reported to NCI DCP monthly for NCI/DCP reporting requirements. The MDS report includes administrative, participant demographic, and adverse event data.
Accrual Quality Improvement and Tracking Program (AQuIP)
AQuIP is a dynamic clinical trial accrual improvement program based upon documented sponsor, study staff, and participant input. AQuIP data collection includes the strategies used to identify each potential participant as well as the reasons for individual screen failures or not enrolling into a trial. AQuIP consists of systematic planning, ongoing evaluation and responsive real-time actions that lead to measurable improvement in the accrual process.
Cancer Data Standards Repository (caDSR)
The caDSR and its associated applications provide centralized documentation to support the data management activities in the research community. It also provides access to common data elements (CDEs) to use when designing systems to capture, report, discover, and use data. The use of CDEs or common information building blocks addresses a biomedical data-management problem: namely, the varied ways in which similar or identical data can be collected and stored in databases. Inconsistency in data representation makes it difficult to aggregate and manage even modest-sized data sets in order to ask basic questions and obtain meaningful answers. The reuse of CDEs facilitates understanding, interpretation, and sharing of cancer research information, development of interoperable systems, and the collection of data generated by disparate experimental platforms. DCP has been using CDEs for approximately 15 years for their studies and has a total of 4,860 CDEs in their context. Each study is broken down into a classification scheme to inform users what CDE is being used for every question on a form or questionnaire.