Learn to navigate complex data structures and efficiently retrieve the data needed to answer a question or solve a problem. Explore the types and sources of healthcare data, along with methods for selecting, preparing, querying and transforming healthcare data. Through video lectures, assignments and discussions, clinical operations analysts will examine the range of data sources and the strategies, tools and methods for data preparation and optimizing data quality. By the end of this course, students will understand the new models of healthcare data organization and analytics, such as clinical registries and query health. In addition, you will learn the basics of SQL programming or improve your SQL skills, within the concepts of other course topics.
Learning Outcomes
- Analyze the various types and sources of healthcare data, including clinical, operational and patient-generated data
- Compare and contrast common data models used in healthcare data systems
- Assess the quality of healthcare data and make appropriate interpretations of meaning according to existing quality frameworks and standards
- Design data models that integrate patient data from multiple sources to create comprehensive, patient-centered views of individual and population data
- Harmonize data from multiple sources and prepare integrated data files for analysis
Skills You Will Gain
- Healthcare data models and representations
- Data selection, preprocessing and querying
- Data harmonization
- Data quality assessment
- SQL Programming
Note: For students starting the Healthcare Analytics Certificate Program, you may take Healthcare Data and Acquisition and Management as your first course if Introduction to Healthcare Analytics is not offered in the quarter you begin the program.