Episode 59: Clinical Data Quality

In this QCast episode, Jullia and Tom look at how clinical data quality is shaped from study set-up through collection, review and integration. They discuss why clear definitions, well-designed data flows and proportionate quality control matter, particularly when trial data move across multiple systems or vendors.Key TakeawaysClinical data should be judged by whether they are fit for the decisions and analyses the study needs to support, rather than by cleanliness alone.Quality problems often begin upstream. CRF design, data definitions, mappings and study instructions can create issues that later queries cannot fully correct.Review effort should focus on critical data and recurring patterns. Trend review can help identify process problems that isolated record checks may miss.🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast.🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode.About QuanticateFounded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in:Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.