Health Information Literacy for Data Analytics

University of California, Davis

This Specialization, "Health Information Literacy for Data Analytics," is designed for data and technology professionals seeking a transition into healthcare data analysis. Over four courses, you will learn to identify, select, and prepare healthcare data for analysis, assess data quality, and create data dictionaries. The program will equip you with the necessary skills to transform raw healthcare data into actionable information.

  • Analyze various types and sources of healthcare data, including clinical, operational, claims, 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 data sources and intended uses.
  • Create a data dictionary to communicate the source and value of data.

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Health Information Literacy for Data Analytics
Course Modules

This Specialization comprises four courses covering healthcare data literacy, data models, data quality and governance, and analytical solutions to common healthcare problems.

Healthcare Data Literacy

This course lays the foundation for a career in healthcare data analytics, covering the value and growing need for data analysts in healthcare, common clinical representations of data, different types of healthcare data, and the complexity of working with healthcare data.

Healthcare Data Models

This course provides insight into healthcare data analytics and the opportunities it holds, giving an overview of common data models and their uses, data integration, clear communication, and measuring and improving data quality in healthcare.

Healthcare Data Quality and Governance

This course explains the importance of data quality in healthcare, detailing how valuable data assets are protected and maintained through data governance to improve healthcare, make it more accessible and affordable, and ultimately save lives.

Analytical Solutions to Common Healthcare Problems

This course covers analytical solutions to common healthcare problems, including organizing data structures, categorizing medical codes, extracting, transforming, and loading data, harmonizing data from multiple sources, and creating a data dictionary to communicate data source and value.

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