Beyond Numbers: Strategic Data Approach for MedTech
Our clinical data management and biostatistics teams bring deep experience and understand the nuances of device performance metrics, diagnostic accuracy parameters, and digital health data streams. Our integrated approach ensures alignment between data collection, management, and analysis—creating a seamless flow from protocol through submission.
Strategic Study Architecture
Our design approach creates robust statistical frameworks and data capture systems tailored to your technology’s unique characteristics, ensuring optimal evidence generation while meeting regulatory expectations.
- Develop technology-appropriate statistical methodologies and sample size calculations including instrument data outputs
- Design specialized endpoint selection based on device performance parameters
- Create custom electronic case report forms optimized for device and procedure data
- Establish validation plans aligned with technology-specific regulatory requirements
- Develop integrated analysis plans for primary and secondary endpoints
- Construct adaptive statistical approaches for evolving technology iterations
Precision Data Collection
Our specialized data collection systems ensure accurate capture of complex MedTech-specific parameters, from device performance metrics to procedural variables, maintaining data integrity throughout the study lifecycle.
- Implement technology-optimized electronic data capture systems
- Train site personnel on proper collection of technical parameters
- Execute real-time data cleaning through sophisticated edit checks
- Manage device-generated data streams with specialized integration tools
- Conduct ongoing data quality monitoring with risk-based approaches
- Implement standardized medical coding using appropriate dictionaries
Powerful Evidence Generation
Our biostatisticians apply advanced analytical methodologies specifically designed for medical technology studies, transforming complex datasets into compelling evidence that supports your regulatory strategy.
- Perform interim analyses with predefined futility and efficacy boundaries
- Conduct comprehensive statistical analysis of primary and secondary endpoints
- Execute specialized device performance and reliability assessment analyses
- Analyze diagnostic accuracy with appropriate statistical analyses of sensitivity/specificity
- Perform complex subgroup analyses to identify optimal patient populations
- Implement Bayesian approaches where appropriate for efficient evidence generation
Submission-Ready Outputs
Our delivery process transforms clinical trial results into reviewer-friendly formats designed to facilitate regulatory understanding and approval, with comprehensive documentation that meets global submission standards.
- Create submission-ready CDISC-compliant datasets with complete documentation
- Develop clear, compelling tables, listings, and figures for regulatory review
- Generate comprehensive statistical reports with thorough methodology descriptions
- Prepare statistical sections for regulatory submissions and publications
- Support regulatory interactions with expert statistical representation
- Develop visual data presentations that effectively communicate complex results
When we came back with the site response regarding the eCRF, our teams quickly assembled to troubleshoot. It was a very collaborative, “think outside the box” meeting. This is a really big win and an example of successful collaboration led by the Beaufort data management team.
Our Data Sciences Difference
We turn complex clinical data into regulatory-ready evidence through tailored structures, integrated strategy, and quality-driven processes—ensuring clarity, accuracy, and confidence across the entire data lifecycle.
Technology-Specific Data Structures
We tailor data systems to the unique requirements of your specific technology category, from procedure-based capture for interventional devices to algorithm performance tracking for digital health.
Integrated Data Strategy
Our comprehensive approach aligns all aspects of data handling from protocol through submission, ensuring the database structure is optimized for final analysis and regulatory requirements.
Quality by Design
We build quality into every aspect of the data lifecycle through comprehensive edit checks, risk-based review procedures, and regular quality assessments.
Regulatory Focus
Every aspect of our data approach is designed with ultimate approval requirements in mind, from submission-ready datasets to presentation formats optimized for reviewer understanding.
