Course Summary
Learn how to make informed decisions in healthcare using data. This course covers foundational concepts in data literacy and how to apply them in a healthcare context.Key Learning Points
- Understand the basics of data literacy and how it applies to healthcare
- Learn how to use data to make informed decisions in healthcare
- Discover how to interpret healthcare data and communicate findings effectively
Job Positions & Salaries of people who have taken this course might have
- USA: $65,000 - $100,000
- India: ₹4,50,000 - ₹12,00,000
- Spain: €30,000 - €50,000
- USA: $65,000 - $100,000
- India: ₹4,50,000 - ₹12,00,000
- Spain: €30,000 - €50,000
- USA: $80,000 - $130,000
- India: ₹7,00,000 - ₹20,00,000
- Spain: €40,000 - €70,000
- USA: $65,000 - $100,000
- India: ₹4,50,000 - ₹12,00,000
- Spain: €30,000 - €50,000
- USA: $80,000 - $130,000
- India: ₹7,00,000 - ₹20,00,000
- Spain: €40,000 - €70,000
- USA: $70,000 - $110,000
- India: ₹6,00,000 - ₹16,00,000
- Spain: €35,000 - €60,000
Related Topics for further study
- Data literacy
- Healthcare decision making
- Data interpretation
- Healthcare data analysis
- Data communication
Learning Outcomes
- Develop a foundational understanding of data literacy
- Apply data literacy skills to healthcare decision making
- Communicate healthcare data findings effectively
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of healthcare
- Familiarity with data analysis tools (e.g. Excel, R, Python)
Course Difficulty Level
BeginnerCourse Format
- Online
- Self-paced
Similar Courses
- Data Analytics for Healthcare
- Healthcare Analytics: Regression in R
Related Education Paths
Notable People in This Field
- Dr. John Smith
- Samantha Lee
Related Books
Description
This course will help lay the foundation of your healthcare data journey and provide you with knowledge and skills necessary to work in the healthcare industry as a data scientist. Healthcare is unique because it is associated with continually evolving and complex processes associated with health management and medical care. We'll learn about the many facets to consider in healthcare and determine the value and growing need for data analysts in healthcare. We'll learn about the Triple Aim and other data-enabled healthcare drivers. We'll cover different concepts and categories of healthcare data and describe how ontologies and related terms such as taxonomy and terminology organize concepts and facilitate computation. We'll discuss the common clinical representations of data in healthcare systems, including ICD-10, SNOMED, LOINC, drug vocabularies (e.g., RxNorm), and clinical data standards. We’ll discuss the various types of healthcare data and assess the complexity that occurs as you work with pulling in all the different types of data to aid in decisions. We will analyze various types and sources of healthcare data, including clinical, operational claims, and patient generated data as well as differentiate unstructured, semi-structured and structured data within health data contexts. We'll examine the inner workings of data and conceptual harmony offer some solutions to the data integration problem by defining some important concepts, methods, and applications that are important to this domain.
Outline
- Healthcare 101
- Course Introduction
- Module 1 Introduction
- Context of Human Systems and Human Biology
- Healthcare Systems
- Opportunities for Improvement: High Costs and Waste
- Opportunities for Improvement: Knowing Doing Gaps
- Opportunities for Improvement: Patient Management
- A Note From UC Davis
- Module 1 Quiz
- Concepts and Categories
- Module 2 Introduction
- Ontologies - Descriptions of the World
- Standard Terminologies
- Diagnoses: ICD-9/10
- SNOMED, CPT, LOINC, Drug Terminologies
- Information Exchange Standards
- Module 2 Quiz
- Healthcare Data
- Module 3 Introduction
- From Concepts to Data: Information to Knowledge
- Clinical Data
- Administrative Data
- Genomic Data
- Big Data
- Module 3 Quiz
- Data and Conceptual Harmony
- Module 4 Introduction
- Data Archaeology
- Data Harmonization
- Data Integration
- Data Mapping
- Entity Resolution
- Course Summary
- Welcome to Peer Review Assignments!
- Module 4 Quiz
Summary of User Reviews
Key Aspect Users Liked About This Course
The course content is comprehensive and easy to understand.Pros from User Reviews
- Great introduction to healthcare data literacy
- Engaging and well-organized course structure
- Instructors are knowledgeable and responsive to questions
- Useful real-world examples and case studies
- Excellent resource for healthcare professionals and data analysts
Cons from User Reviews
- Some sections may be too basic for experienced data analysts
- Could benefit from more interactive elements
- Lack of practical exercises or assignments
- Limited focus on specific healthcare data tools or software
- Some technical jargon may be difficult for beginners
Brian Paciotti
4.5 Raiting
Healthcare Data Literacy
- 4.5
-
![]()
![]()
![]()
![]()
![]()
This course will help lay the foundation of your healthcare data journey and provide you with knowledge and skills necessary to work in the healthcare industry as a data scientist....
Business Analytics Executive Overview
- 4.6
-
![]()
![]()
![]()
![]()
![]()
Businesses run on data, and data offers little value without analytics. This course will focus on understanding key analytics concepts and the breadth of analytic possibilities....
