The Health Data Quality Program delivers a comprehensive series of online trainings that cover key aspects of using health data in clinical research including hospital information systems and electronic health record, data protection regulations, clinical research informatics, interoperability, as well as data quality assessment and monitoring in clinical trials. The program is designed for healthcare professionals who routinely capture health data, and for clinical research personnel who use health data to plan and execute clinical trials. The content of the program helps to understand the value of that data to the organization and to patients, for safe and effective continuity of care and for clinical research. The program has been designed by a multidisciplinary consortium supported by EIT Health.

EIT Health

Course code: 1113

Through concrete examples of data quality issues, this course will explain and illustrate the use cases for which computable health data can be useful and crucial. This is where you can further expand your knowledge of assessing and measuring data quality. You can also discover the different factors that are affecting data quality and the strategies and statistical methods to compensate and improve the quality of health data.

This course will also discuss opportunities from big data for learning health systems and touch on regulations such as the GDPR.

Duration: ~7 hours

This course is available now.

Course code: 1111

This course will take you through a patient’s journey in a hospital and initiate you into the hospital information system and electronic health record (EHR). Aside from familiarizing you with the medical informatics terms and digital health standards, this course is illustrated through several success stories of innovative EHR and new trends in clinical decision support system (CDSS).

Duration: ~50 minutes


Course code: 1112

This course will provide an inside look at clinical trials and the digital technologies that are transforming them. These include electronic data capture systems, clinical data warehouse, registries, real world evidence, and artificial intelligence/machine learning.

Duration: ~3.8 hours