Teaching

The Quantitative Biomedical Sciences Program

QBS 192: Health Informatics

Our health is everywhere. It is affected by how, where, and who we live, work & play with (i.e. biological, behavioral, social, and environmental factors). The explosion of digitization of data captured both outside ‘in the wild’ and within the healthcare delivery system, allows us to understand and address the many factors affecting the complexity of our health. Today, health & healthcare data is continuously being generated. Data may be generated by healthcare delivery systems, organizations, or users and accessed directly through devices, databases, or APIs. Deriving information and knowledge to improve and maintain health requires health informatics. Data Science plays an active role as a profession and within its research efforts in informing and developing all aspects of health informatics: data capture, data storage, and data analytics.

The goal of this course is two-fold: first, to learn about the latest topics in health informatics and second, to design and develop a health informatics project. Special topics in health informatics will be introduced through lectures and primary literature. These topics will be organized into 4 themes: 1.) Applications Theme: exploring several key current applications of health informatics, 2.) Data Capture Theme: learning about data capture technologies and standards, 3.) Data Storage Theme: presenting data formats, databases, and issues of security & privacy, 4.) Data Analytics Theme: a brief introduction to the data analytics cycle and special topics of visualization and analytics methodologies.

The Dartmouth Institute Program

PH 109: Systems Thinking

We live, work, and play embedded within physical, social, and cyber systems of systems. These systems can be natural, technical, or a combination. They can be simple or complex and can lead to predictable or unpredictable emergent system behavior such as poverty, health disparity, chronic disease, etc. Specialization in academics lends itself to reductionist thinking—breaking the problem into pieces and focuses on understanding the parts to understand the whole. Such a thinking paradigm has prevented us from solving some of the real-world challenges we face today—global warming, pandemics, etc. Solving real-world problems requires a view of the system or systems-of-systems to understand the whole to more precisely make changes that lead to intended system behaviors.

This course provides a hands-on introduction to systems thinking and modeling. We live, work, and play embedded within physical, social, and cyber systems of systems. Students will develop systems thinking skills as they model natural, technical and, socio-technical systems at various scales and scope, from the home to a national public health system. Topics include: Why do we need systems thinking?, what is a system?, types of systems, key system concepts, modeling the graphical architecture of a system, and a brief description of system tools.