Ethics

This chapter provides an overview of pertinent Ethics topics for the field of health analytics and informatics. We first start with a brief introduction to Ethics in general and the issues pertaining to Data Ethics. This includes how to appropriately present data, and visualize results in a manner that is understandable and transparent. This will also include when to conduct a study, and when there are biases that exist in a particular study. We will then discuss the topic of inferring genetic risk from published research and the gaps that exist in genetics specifically around the lack of diversity. This lack of diversity can affect the interpretation of the genetic results in populations that have not been studied previously. We will also touch on healthcare disparities and the impact that those disparities can have on health analytics studies. This goes beyond the impact of genetics and the lack of diversity within genetic studies but touches on issues such as structural Racism and how that can impact human health and disease risk. Finally, we will discuss reproducibility and transparency of research results; this includes both the data themselves and the code and analysis scripts. After reading this chapter, you should be able to confidently answer the following questions, and understand the following material: