Course Summary
This course covers the application of data science in the field of health informatics. Students will learn how to analyze and interpret healthcare data, and use it to improve patient outcomes and healthcare delivery.Key Learning Points
- Understand the fundamentals of healthcare data and information systems
- Learn data science techniques and tools for healthcare analytics
- Apply data analysis to improve healthcare outcomes
Related Topics for further study
- Healthcare Analytics
- Data Science Techniques
- Healthcare Information Systems
- Patient Outcomes
- Healthcare Delivery
Learning Outcomes
- Analyze healthcare data using data science techniques
- Evaluate healthcare information systems to improve patient outcomes
- Apply data analysis to improve healthcare delivery
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of statistics
- Familiarity with healthcare terminology
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Healthcare Data Literacy
- Healthcare Analytics Foundations
Related Education Paths
Related Books
Description
Health data are notable for how many types there are, how complex they are, and how serious it is to get them straight. These data are used for treatment of the patient from whom they derive, but also for other uses. Examples of such secondary use of health data include population health (e.g., who requires more attention), research (e.g., which drug is more effective in practice), quality (e.g., is the institution meeting benchmarks), and translational research (e.g., are new technologies being applied appropriately). By the end of this course, students will recognize the different types of health and healthcare data, will articulate a coherent and complete question, will interpret queries designed for secondary use of EHR data, and will interpret the results of those queries.
Knowledge
- Articulate different forms of clinical and population level data.
- Describe the data required to answer a healthcare information problem.
- Distinguish between data questions and data queries when dealing with a healthcare information problem.
Outline
- Introduction to Databases and Data Types
- Introduction to Databases
- Databases in Clinical Informatics
- Common Data Types I
- Common Data Types II
- Common Data Types III
- Emerging Data Types
- Module 1 Quiz
- Data Sources and Data Challenges
- Common Clinical Data Sources
- Population-Level Data Sources
- Data Challenges I
- Data Challenges II
- Data Challenges III
- Module 2 Quiz
- Formulating Data Questions
- Formulating a Data Query I
- Formulating a Data Query II
- Real World Data Questions
- i2b2 Demo
- HealthData.Gov Demo
- HCUPNet Demo
- Module 3 Quiz
- Real World Applications of Data Science in Health Informatics
- Introduction
- Interview with Sam Meiselman
- Interview with Sam Meiselman, Part II
- Interview with Bonnie Woods
- Interview with Brandyn Lau, Part I
- Interview with Brandyn Lau, Part II
- Interview with Brandyn Lau, Part III
- Wrap Up
- Module 4 Quiz
Summary of User Reviews
The Data Science of Health Informatics course on Coursera has received positive reviews from many users. The course covers a variety of topics related to health informatics and data science. One key aspect that many users thought was good is the comprehensive approach to teaching the subject matter.Pros from User Reviews
- Comprehensive approach to teaching the subject matter
- Great instructors with extensive knowledge
- Course content is relevant and up-to-date
- Opportunities to apply what you learn in real-world scenarios
Cons from User Reviews
- Some technical concepts may be difficult for beginners to understand
- The course can be time-consuming
- Limited interaction with instructors and other students
- Some assignments may be challenging and require additional research
- The course may not be suitable for those without a background in data science or health informatics
Hadi H. K. Kharrazi, MD, Ph.D
4.7 Raiting
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