SAS Clinical Data Management
At Squircle, our clinical data management and consultancy services are dedicated to providing you with clinical data, data analysis, and regulatory support and presentation requirements.
The increasing role of a dedicated Clinical Research Organization in your company’s clinical data requirements.
At Squircle, our clinical data management and consultancy services are dedicated to providing you your clinical data, data analysis, regulatory support and presentation requirements. Within clinical data management, optimal therapeutic designs, customer support and customized data analysis are key areas where our bio statisticians and medical writers interact to provide comprehensive solutions. Only through an all-inclusive understanding of study objectives, clinical design issues, and upgraded quality control measures, can maintenance of the quality of data and adherence to expected deadlines be achieved. Analysis of clinical trials includes pharmacokinetic and dynamic evaluations, therapeutic equivalence testing and sequential designs.
SAS Clinical Data Management Services
- Data entry cleaning
- Case report form review
- Automatic edit checking and query tracking
- Medical Coding
- Coding of adverse events (meddra, who-art, costart)
- Coding of concomitant drugs (who drug centralized data coding)
- Clinical Database locking
- Clinical Data transfer specification (CDISC-SDTM and Sponser specific)
SAS Clinical Data Integration
- Integrates clinical, operational and safety data from multiple sources.
- Protects your investment in legacy operational systems and data.
- Integrates with Medidata Rave® and other leading EDC systems.
- Enables access to all data regardless of source or format.
- Automates data loads for clinical data on a more frequent schedule.
Prepares uniform, consistent data for analysis.
- Includes flow control, integrated error reporting, job performance monitoring and statistics, and
- Provides tools to support aggregation of data across clinical trials.
- Provides a full mapping of data source (where data came from), data
manipulations (how the data has been manipulated) and the final destination for data.
- Helps you plan for and report on the impact of any process changes, including:
- Changes to incoming data formats.
- Changes in data standards.
- Additional data requirements for analysis data sets.
Enhances data quality to ensure trustworthy analytically conclusions.
Automates data quality activities so less time is spent validating incoming clinical data.
Automatically incorporates data quality techniques to ensure consistent, trusted and verifiable clinical information.
Supports data standards and performs adherence checks.
- Performs standards adherence checks.
- Includes prebuilt support for CDISC models, including SDTM and CRT-DDS (define.xml), and is extensible for custom models.
- Provides specialized transformations for mapping clinical data to a standard model.