This course serves as an intensive introduction to the most central technical tools of Informatics – Structured Query Language (SQL), data structures, optimization, data visualization, simulation models, probabilistic and statistical thinking, and machine learning. The course teaches data management using SQL, processing, statistical analysis, and basics of machine learning using Python.
Dr. Purkayastha redesigned this course in the Fall 2017
EXTENDED COURSE DESCRIPTION
This course introduces the most central technical tools of informatics, which encompasses bioinformatics and health informatics. It will serve as an introduction to programming, as well as computational thinking using Python 3. Bioinformatics focuses on translational research that uses computational means to transform biological data into discoveries that help us better understand and improve life. Health informatics enhances human health and well-being through the use of information technology, computer science, and knowledge management to deliver more efficient and safer patient care as well as improve patient and population outcomes. Electronic health records, telemedicine applications, mobile health (m-health) applications, and clinical
decision support are among the many technologies found in health informatics. We will perform database management functionality, learn data analysis algorithms, understand informatics research methods, and apply quantitative research methods in the course project.
This course introduces the use of patient data, genomic databases, and electronic health records (EHR) to improve patient care and to achieve greater efficiencies in public and private healthcare systems. The course explores clinical intelligence and the role of analytics in supporting a data-driven learning healthcare system. Topics include the value-driven healthcare system, measuring health system performance, existing quality/performance measurement frameworks (NQF, HEDIS), comparing healthcare delivery, attributes of high performing healthcare systems, and the IT infrastructure and human capital needed to leverage analytics for health improvement.
This 1-3 credit course is designed for graduate students that are about to start their thesis. The student prepares and presents a thesis on an area of health informatics. The thesis is a substantial, typically multi-chapter scientific paper of a carefully designed and evaluated application, based on well-planned research.
This 3 credit course is designed as an introductory course to database design with an emphasis on managing data in the health information environment. Topics include using a relational database system to create tables and relationships, perform normalization, and generate user forms and reports. Students conduct a large group project. This course was redesigned by Dr. Purkayastha in Fall 2015, with new MySQL and OpenMRS course content. This course is used to do research related to teaching and learning pedagogy using POGIL (Process Oriented Guided Inquiry Learning)
This course is approved for the Analytical Reasoning component of the General Education core.
A 3 credit course is designed to discuss the basic structure of information representation in digital information systems. It covers three modules: web development, relational databases, and XML technologies. Through this course, students are able to develop web pages that can interact with the backend servers; represent relational databases in the ER model, query the data using the formal query language SQL; and use XML technologies to store and display data.
This was taught by Dr. Purkayastha only in Fall 2015 and is not taught by him anymore.
This course will introduce the foundation of Health Informatics. It will review how information sciences and computer technology can be applied to enhance research and practice in healthcare. The basic principles of informatics that govern communication systems, clinical decisions, information retrieval, telemedicine, bioinformatics, and evidence-based medicine will be explored.