Oomnia EDC
Optimized Electronic Data Capture for clinical research trials
Effective and efficient trial management. Your way
Oomnia EDC is a unique, fully digitized solution for collecting, cleaning, and reviewing clinical trial data. The data integration capabilities, customized dashboards, and real-time reports enable you to oversee and manage your Clinical Trial effectively and efficiently.
Oomnia EDC is designed to support the process of clinical trials throughout their lifecycle. Paired with Oomnia’s other features, our EDC module provides you with a flexible, versatile, integrated, role-specific and accessible platform with customized dashboards per role to facilitate clinical trial data and operational oversight.
Benefits
Interoperability
Data interoperability allows seamless data exchange and automated cleaning, reducing redundant and error-prone actions.
Reusability
Reuse eCRF templates, roles, settings, and variables easily across multiple trials.
Real-Time Reports
Customized downloadable reports and email notifications.
Solutions
Cloud Database
Cloud-based EDC ecosystem creates synergies along the entire clinical trial life cycle. All data is stored in a centralized cloud database, with the capability to create separate, secure country- and region-specific cloud databases to comply with local data sharing regulations.
Intrinsic and Extrinsic Integration
Data integration across designated eCRFs reduces duplicate data entry, and integration of external data within EDC further facilitates study oversight, automated data cleaning, and reconciliations.
Alignment with CDISC standards
The EDC module is designed with pre-programmed data collection groups based on CDISC standards, allowing each eCRF to be fully customized per eCRF page using a drag-and-drop functionality aligning with CDISC standardization.
Increased efficiency across Users
Capability for single sign-on access to all assigned trials within EDC, with the flexibility to use the previously defined User Roles or to create new study-specific definitions. Template User Role definitions can easily be updated per eCRF page, in addition to corresponding report and dashboard templates per User Role.
Features
Integration
Oomnia’s EDC integration engine is capable of integrating data from various sources, including but not limited to: electronic health records, medical device data (including wearables), central and local laboratories, ePRO, drug assignment and accountability.
Customized Reports and Dashboards
Standard template reports can easily be customized to meet Client and User needs per study. New reports can also be created to incorporate additional data or to present the data in different outlays to facilitate study oversight, monitoring, and reporting. Dashboards are created to be User-specific, providing the most critical study status updates upon sign-on.
SAE Reporting
Designated eCRFs can be utilized to capture Initial, Follow-Up, and Final SAE Reports directly within EDC.
Automated Data Cleaning
Our technology includes advanced edit checks during data entry and across eCRF pages. Each eCRF will only display the required data fields when applicable based on data entries for previous fields.
User Roles
User roles are defined for each study, with granular access and privilege settings that can be applied per eCRF. These Role settings can be saved and reused in the future, or they can be redefined.
Intuitive, User-Centered Design
Intuitive user-centric design minimizes requirements for training and support requests, facilitates faster data entry and data cleaning, and reduces overall time spent on data capture efforts. Our EDC solution is designed with the end user in mind. Therefore, we paid particular attention to efficiency, effectiveness, error tolerance, and ease of learning. As a result, users are provided with a more manageable data capture process, with fewer queries and redundancies.
Audit Trails
Our audit trails are visible within each eCRF. The Data Manager can also export the audit trails in various file formats, which are easily understood for study team members, but also suitable for computed analytics.
