Master the Next Generation of Clinical Research: 5 Strategies to Dramatically Improve Data Quality

Five strategies for clinical data quality, covering data management, risk based quality management, AI assisted review and proactive error detection.
May 8, 2024
11am (ET) / 10am (ET)
OVERVIEW

Advances in clinical research over the last decade have given rise to an intricate patient data ecosystem, presenting enormous opportunities for clinical research professionals to create a more complete view of the patient. One key challenge, however, lies in integrating and managing those sources to deliver high-quality data, faster. How do we overcome this?

In this session, we will unravel the complexities of fragmented data systems, emphasizing the urgent need to adopt technology and processes that harmonize diverse data sources and ensure quality throughout the clinical data lifecycle. You’ll discover how to unify data management and risk-based quality management approaches,  and augment processes with advanced technologies like AI to rectify manual data entry errors more efficiently and ensure overall quality end-to-end.

 

Join this webinar to learn five strategies to help you adopt a clinical data quality framework that addresses the complexity of the modern clinical data landscape.

Addressed Challenges

01Overcoming the top organisational challenges of adopting an end-to-end clinical data quality strategy across fragmented systems and data sources. 
02Identifying and implementing the right technology and process recommendations to overcome common roadblocks in clinical data quality management. 
03Ensuring successful adoption of clinical data quality frameworks by end users across sites, functions, and clinical operations teams. 

WHAT YOU WILL LEARN

01Learn how to move from manual, reactive data review to proactive risk-based approaches built on integrated and harmonised clinical data sources. 
02Discover workflows and analytics that support clinical data management and monitoring teams in their day-to-day trial execution responsibilities. 
03Understand how AI-enabled technologies can automate manual data tasks and identify potential data quality issues earlier across the clinical data lifecycle. 
Reserve Your Seat
SPEAKER
Clinical Data Quality Webinar
Ken Hamill
Senior Director Clinical Operation Portfolio, Medidata
Ken has worked within the Life Sciences technology space for over 16 years across discovery, preclinical, and clinical areas. At Medidata, his focus includes launching and commercializing solutions in trial management and risk-based quality management (RBQM) which streamline clinical execution processes. He works across the organization and with customers in their adoption of enabling technologies that enhance efficiency and deliver deeper insights to improve trial quality and patient safety. Ken is a subject matter expert on RBQM processes. Prior to Medidata Ken was a strategy director at PerkinElmer, where he led the commercialization of drug discovery assay solutions. Ken has an MBA and an MS in Chemistry.
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