Applied Clinical Informatics II: Computer Science Fundamentals and Data Analytics; Challenges in Informatics Quality and Safety.

In this course students learn advanced health data science concepts necessary to design, develop, implement and administer new technologies specifically targeted towards improving healthcare outcomes. Healthcare data integrity, data quality, and data portability are emphasized. Management of data structure and content for compliance with existing and emerging standards for interoperability and big data set creation, are highlighted. Students examine strategies and technologies for data storage, data exchange, data normalization, and data re-use for research, quality improvement and patient care. This course explores different strategies for representing data, information and knowledge, including required and emerging standards for coding and nomenclature, and their associated taxonomies and ontologies. It also examines how these standards are used in tools for mining, analyzing, interpreting and sharing information for a variety of clinical and administrative purposes throughout the healthcare system. This course provides students the opportunity to explore state of the art health care technologies such as electronic phenotyping, cloud-based real-time clinical decision support, natural language processing using artificial intelligence, machine learning tools used to analyze large data sets in distributed research networks.