Healthcare Data Literacy by Coursera

This course will lay the foundation for your healthcare data journey. It will also equip you with the knowledge and skills required to work as a data scientist in the healthcare industry. Healthcare is unique in that it involves complex and constantly evolving processes related to medical care and health management. We will learn about all aspects of healthcare and the growing demand for data analysts in the field. We will learn more about the Triple Aim, and other data-enabled health care drivers. We will discuss the different categories and concepts of healthcare data. We will also explain how terminology and taxonomy organize concepts and make computations easier. We will discuss common clinical representations of healthcare data, such as ICD-10, SNOMED and LOINC, as well as drug vocabularies (e.g. RxNorm) and clinical data standards. We will discuss the many types of healthcare data as well as the complexity of pulling together all of the data needed to make decisions. We'll analyze different types of healthcare data including operational and clinical claims and patient-generated data. Additionally, we will distinguish between structured, semi-structured, and unstructured data within the context of health data. We will examine the inner workings and offer solutions to the problem of data integration by defining important concepts, methods and applications.