LII:Data Analytics and Visualization in Health Care

Title: Data Analytics and Visualization in Health Care

Author for citation: Travis Masonis

License for content: Unknown

Publication date: 2024

This is a Rochester Institute of Technology (RIT) course that is released on the edX platform. The eight-week course is designed for students to learn how "to extract, analyze, and interpret data from patient health records, insurance claims, financial records, and more to tell a compelling and actionable story using health care data analytics." The course is free to take, with a Verified Certificate of completion available for $249. The course requires on average eight to 10 hours a week of effort. The next class begins on July 7, 2024, ending November 29. The free audit track will likely expire in early September.

The edX course description:

"Big data is transforming the health care industry relative to improving quality of care and reducing costs--key objectives for most organizations. Employers are desperately searching for professionals who have the ability to extract, analyze, and interpret data from patient health records, insurance claims, financial records, and more to tell a compelling and actionable story using health care data analytics.

The course begins with a study of key components of the U.S. health care system as they relate to data and analytics. While we will be looking through a U.S. lens, the topics will be familiar to global learners, who will be invited to compare/contrast with their country's system.

With that essential industry context, we'll explore the role of health informatics and health information technology in evidence-based medicine, population health, clinical process improvement, and consumer health.

Using that as a foundation, we'll outline the components of a successful data analytics program in health care, establishing a "virtuous cycle" of data quality and standardization required for clinical improvement and innovation.

The course culminates in a study of how visualizations harness data to tell a powerful, actionable story. We'll build an awareness of visualization tools and their features, as well as gain familiarity with various analytic tools."

About the authors

The instructor for this course is Travis Masonis. See the professor's profile for full details.

General layout and contents of the course

The course is split into four modules:

1. Introduction to Health Care - This module begins with a discussion of what health care is, who its stakeholders are, and the functions it serves. It then goes into the goals and challenges associated with health care provision; the approaches and ethics of health care; and the demographics, economics, and current trends involved in the industry.

2. Introduction to Health Informatics - This module starts by providing an overview of the information technology (IT) behind the scenes in healthcare, as well as how the technology supports health care's goals. Then details of its various systems and data are provided, as well as the adoption rates, regulations, standards, and user engagement of those systems.

3. Introduction to Data Analytics - This third module introduces the concepts of data, big data, and the associated analysis. It includes discussions on data cleanliness and compilation, information privacy and security, data analysis using current technology, and data practicality issues.

4. Introduction to Visualizations - The final module taps into data visualization and its value to health care stakeholders. The module dives into visualization best practices, use cases, and designs. It includes discussions of exploratory vs. explanatory and quantitative vs. qualitative visualizations within the realm of healthcare. The module concludes with a review of common data analysis and visualization tools, as well as software benchmarking.

The course

: The course can be found on the edX site, under the Data Analysis & Statistics category. The next class begins on July 7, 2024, ending November 29. The free audit track will likely expire in early September.