What you'll learn:
- Introduction to Health Data - sources, types, uses
- Introduction to Diagnosis, medical procedure, drug, laboratory codes
- Features of health data that enhance analyses
- Issues with health data and how to practically handle these
This is an introductory course for Health Data, from the perspective of data analysts.
The content is pitched at entry level health data analysts.
Data characterizes, and connects complex health care systems.
A thorough understanding of health data is fundamental to health analytics, which in turn turns raw health data into actionable insights. There are also features of health data that are pertinent to making effective use of it. Though there are plenty health data, there persists issues that must be address in order to scaleably perform subsequent analyses.
Through this course, you will
gain a highly valuable skill in the healthcare sector
understand how health data records information about each patient and medical encounter
learn a few features of health data that enable you to perform more insightful analyses
be able to communicate more effectively with clinical and analytic colleagues
be empowered to improve care processes and make a difference to many people’s health and lives
The 4 sections we will cover
Where health data come from: 5 main sources including health insurance claims, EHR, research reports, public health, user generated
What health data look like: Structured and Unstructured data, including diagnosis, procedures, drug, LOINCcodes
Features of health data: Hierarchical structures, Disease etiology, chronology, supply vs demand
Issues of health data: Gaps, Errors, and how to practically deal with these
NEW!!!2 Bonus Sections from my Predictive Modeling course on Planning and Getting buy in for an analysis.
