Åsa Testad’s career began with a background in informatics and programming—skills that today serve as the foundation of her work in clinical studies. After entering the field in the late 1990s, Åsa transitioned into data management and found a role that combined problem-solving, structure, and collaboration.
“My role involves working at the intersection of different teams—Clinical Project Managers, statisticians, monitors, physicians, and the manufacturer—to make sure we collect, manage, and validate data efficiently and accurately,” Åsa explains. “It’s about creating structured, reliable data that supports strong clinical evidence.”
At GBA Key2Compliance, Åsa brings together technical precision and human insight to help clients build smarter data strategies—ones that are not only compliant but practical and patient-centered.
What is Clinical Study Data and Why Does It Matter?
In clinical studies, data is the foundation of everything—from regulatory approvals to patient safety assessments and proving the efficacy of a medical device. Clinical study data is collected from various sources, including:
- Electronic Case Report Forms (eCRFs): Digital systems where investigators enter patient data from clinical visits.
- Patient-Reported Outcomes (PROs): Data provided directly by patients about their symptoms and experiences.
- Medical Device Readings: Data generated from diagnostic tools, wearables, or implantable devices.
- Lab Results: Blood tests, biomarkers, and other diagnostic parameters that support clinical findings.
- Imaging: data from different types of imaging, e.g., CT and MRI
- Adverse Event Reports: Information about any side effects or unintended reactions observed during the study.
The goal is to collect data in a structured, accurate, and compliant manner so that the findings can be trusted by regulatory authorities and healthcare professionals. However, too much data—or poorly structured data—can lead to inefficiencies, higher costs, and even regulatory setbacks.
The Cost of Data: Why ‘Less is More’ in Clinical Studies
One of Åsa’s core insights is that more data isn’t always better—in fact, it can be a costly mistake.
“Many companies believe that collecting as much data as possible will give them an advantage, but they often underestimate the cost associated with it,” Åsa says. “Every single data point requires programming, validation, and monitoring—and can place an unnecessary burden on both site staff and patients.”
She has seen sponsors request extensive free-text fields or broad exploratory data, only for it to go unused. Worse, unstructured data can introduce compliance risks or even mask safety signals.
“We always ask: ‘What are you trying to prove?’ If the data doesn’t support a claim or regulatory need, it may not be worth collecting.”
Planning for Compliance from the Start
Åsa emphasizes that effective clinical data management starts long before the first patient is enrolled. Early planning, thorough testing, and risk-based validation are essential.
“If I could give companies one piece of advice, it would be this: document what you do and why you do it. That clarity helps everyone—especially when team members change midway through a study.”
Her structured approach includes:
- Designing a clear data flow for the entire study lifecycle
- Validating systems and tools before launch
- Collaborating closely with clients to align on what data is essential
“Think of compliance as a roadmap. The clearer your plan, the smoother your study.”
Want to understand the fundamentals of planning a clinical investigation of a medical device?
Download our free Beginner’s Guide to Clinical Investigation Plans for step-by-step guidance.
Balancing Innovation and Structure
Like many in the industry, Åsa is watching the rise of AI with curiosity—but also caution.
“AI has potential in areas like coding or pattern recognition, but when it comes to cleaning or interpreting clinical data, human oversight is still essential,” she says. “We need to understand what’s being flagged, and why — otherwise we risk introducing bias.”
Instead of chasing trends, Åsa focuses on what’s proven to work: clear objectives, structured systems, and collaborative teams.
Supporting Smarter, Patient-Centered Studies
Åsa’s approach is grounded in years of hands-on experience across a wide range of studies. She’s seen firsthand how a well-planned data strategy can reduce delays, improve quality, and ease the burden on study sites.
”Focusing on what truly matters, at the right time, leads to stronger studies and faster results.” This is why, when resources are tight, timing becomes important. The right support at the right time can be the difference between a smooth process and a six-month delay.
The Value of Expert Partnership
Strategic guidance from day one → Fewer delays, fewer regulatory issues
- More structured data → Higher quality for analysis and reporting
- Optimized data processes → Cost-effective, streamlined clinical studies
- Compliance without overcomplication → Smarter, focused data collection
We understand that balancing regulatory demands, limited resources, and patient experience is not easy. That’s why our MedTech CRO services are designed to meet companies where they are and support them where it counts most:
- Helping clients structure data strategies from the start
- Supporting study design and regulatory planning
- Ensuring endpoints align with approval goals
- Implementing robust EDC systems for compliant data capture
- Optimizing recruitment strategies and site monitoring
Collecting clinical study data doesn’t have to be overwhelming. With the right support, companies can build confidence in their processes—and in their results.
Need support optimizing your clinical study data strategy?
Get in touch with our team today!
Want to learn more about our expertise in clinical research and regulatory strategy?
Read our interview with Senior Consultant Emily Malmberg, where she shares how to navigate IVDR with confidence.