Health Data Quality

Ensuring high-quality data seems evident and straightforward, but unfortunately, this is not the case in practice. Routinely collected health data today is of variable quality, and is often not fit for reuse purposes. Which affects clinical research, decision making and patient outcomes. How can you scale up your data quality?


I. Introduction to Health Data Quality and Data Protection

Through concrete examples of data quality issues, this topic explains and illustrates the use cases for which computable health data can be useful and crucial. It will also discuss opportunities from big data for learning health systems and touch on regulations such as the GDPR.

II. Clinical Research and Clinical Research Informatics

This topic provides 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.

III. Patient Care and Electronic Health Record (EHR)

This topic goes through a patient’s journey in a hospital and introduces the hospital information system and electronic health record (EHR). Aside from familiarisation with the medical informatics terms and digital health standards, this topic is illustrated through several success stories of innovative EHR and new trends in clinical decision support system (CDSS).