Brief Introduction
Learn best practices in data analytics, informatics, and visualization to gain literacy in data-driven, strategic imperatives that affect all facets of health care.
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.
Knowledge
- Identify current forces disrupting today's health care industry
- Summarize current health care trends and their impact on cost, quality, and patient engagement
- Describe health informatics' role in clinical workflow and patient engagement
- Identify components of health information technology
- Explain the importance interoperability in health care analytics
- Summarize data collection, processing, and analysis best practices
- Explore the implications of artificial intelligence on extraction and analysis of complex data sets
- Interpret data analysis results from a visualization example
- Identify visualization best practices
- Prepare a simple data visualization using health care data
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