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Doug Berman
Career prospects are bright for those qualified to work in healthcare data analytics. Perhaps you work in data analytics, but are considering a move into healthcare where your work can improve people’s quality of life. If so, this course gives you a glimpse into why this work matters, what you’d be doing in this role, and what takes place on the Path to Value where data is gathered from patients at the point of care, moves into data warehouses to be prepared for analysis, then moves along the data pipeline to be transformed into valuable insights that can save lives, reduce costs, to improve healthcare and make it more accessible and affordable. Perhaps you work in healthcare but are considering a transition into a new role. If so, this course will help you see if this career path is one you want to pursue. You’ll get an overview of common data models and their uses. You’ll learn how various systems integrate data, how to ensure clear communication, measure and improve data quality. Data analytics in healthcare serves doctors, clinicians, patients, care providers, and those who carry out the business of improving health outcomes. This course of study will give you a clear picture of data analysis in today’s fast-changing healthcare field and the opportunities it holds for you.
Register for this course and see more details by visiting:
OpenCourser.com/course/2y7p68/healthcare
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What's inside
Syllabus
Introduction to Healthcare Data Models
In this module, you will be able to define the foundational terms used in discussing and building healthcare data models. You'll be able to describe the conceptual model showing how data flows from operations to analysis. You will compare and contrast common data models used in healthcare data systems. You will also be able to identify common measures used in healthcare data analysis.
Read more
Syllabus
Introduction to Healthcare Data Models
In this module, you will be able to define the foundational terms used in discussing and building healthcare data models. You'll be able to describe the conceptual model showing how data flows from operations to analysis. You will compare and contrast common data models used in healthcare data systems. You will also be able to identify common measures used in healthcare data analysis.
Read more
Data Models and Use Cases They Support
In this module, you'll be able to describe the Star Schema Data Model, distinguish it from the hierarchical and relational model, list some pros and cons and explain situations in which it could be appropriately used. You should also recognize when another type of data model might be better suited to a particular use case.
Working with Data across Systems
In this module, you'll be able to explain how information is stored in data models and how we assemble relevant information to analyze an interesting problem that can improve our healthcare systems. We'll review how we normalize data and how that facilitates analysis. We'll go on to discuss how to bring together information from different sources and across various functional systems. We will also consider how to measure it accurately.
Improving the Quality of Healthcare Data
In this module, you will be able to examine the data that goes into these models and explain how we work with the information that comes from the practice and business of medicine. We will transition from raising the data quality to focusing on finding and correcting data errors by validation and verification. You will also be able to describe several ways data is checked to eliminate errors and improve data quality.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores a relevant topic in healthcare data analytics and its impact on the industry
Develops valuable skills desired by healthcare industry employers, including data analysis and communication
Provides a strong overview of healthcare data models, enhancing foundational understanding
Emphasizes the importance of data quality and validation, fostering attention to detail and precision
May require familiarity with basic healthcare principles and terminology
Save this course
Save Healthcare Data Models to your list so you can find it easily later:
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Reviews summary
Informative overview
Learners say this foundational course offers a good overview of healthcare data models. The course is basic and introductory, suitable for beginners or as a refresher. Most students find the course engaging and informative, but some wish it had been more in-depth.
Engaging and informative
"amazing course"
"Excelent course about quality of data in heathcare."
Basic, introductory level
"Course is good but at a very basic level."
"Intro level. "
Could be more in-depth
"Little more technical depth around developing a healthcare data model would have been useful"
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Healthcare Data Models with these
activities:
Compile a resource list
Show steps
Create a comprehensive list of resources, such as websites, articles, and books, related to healthcare data analytics.
Show steps
-
Search for resources using online search engines and databases
-
Review the resources and select the most relevant ones
-
Organize the resources by topic or theme
-
Share the resource list with classmates or post it online
Review healthcare data analytics underpinnings
Show steps
Review the foundational knowledge required to succeed in this course, such as general data analysis techniques, healthcare terminology, and data modeling principles.
Browse courses on
Healthcare Data Analytics
Show steps
-
Read the course syllabus and textbooks
-
Attend the first few lectures and make notes
Practice data modeling exercises
Show steps
Gain hands-on experience creating and manipulating data models using industry-standard tools.
Browse courses on
Data Modeling
Show steps
-
Complete the exercises provided in the course materials
-
Find additional exercises online or in textbooks
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a study group
Show steps
Collaborate with peers to discuss course concepts, solve problems, and reinforce learning.
Show steps
-
Find classmates who are interested in studying together
-
Set regular meeting times and locations
-
Prepare for each meeting by reviewing the course materials and completing any assigned exercises
-
Actively participate in discussions and ask questions
Become a mentor to other students
Show steps
Share your knowledge and skills by mentoring other students in the course.
Show steps
-
Contact your instructor or classmates to express your interest
-
Match with a student who needs help
-
Meet regularly to provide guidance and support
-
Encourage your mentee to ask questions and seek clarification
Attend online workshops and webinars
Show steps
Supplement your learning with expert-led workshops and webinars on healthcare data analytics.
Show steps
-
Search for online workshops and webinars
-
Register for and attend the events
-
Take notes and ask questions
-
Apply what you learn to your own projects
Design a data analysis plan
Show steps
Develop a comprehensive plan outlining the steps involved in data analysis, from data collection to interpretation.
Browse courses on
Data Analysis
Show steps
-
Identify the research question and objectives
-
Choose appropriate data sources and methods
-
Design a data collection strategy
-
Develop a data analysis plan
-
Write a data analysis plan document
Build a healthcare data analytics portfolio
Show steps
Create a portfolio of data analytics projects that demonstrate your skills and knowledge in healthcare.
Browse courses on
Data Analytics
Show steps
-
Choose a project that interests you and is relevant to the field of healthcare
-
Gather data and explore it
-
Develop a data analysis plan
-
Analyze the data and draw conclusions
-
Create a presentation or report of your findings
-
Reflect on your project and identify areas for improvement
Compile a resource list
Show steps
Create a comprehensive list of resources, such as websites, articles, and books, related to healthcare data analytics.
Show steps
Show steps
Show steps
- Search for resources using online search engines and databases
- Review the resources and select the most relevant ones
- Organize the resources by topic or theme
- Share the resource list with classmates or post it online
Review healthcare data analytics underpinnings
Show steps
Review the foundational knowledge required to succeed in this course, such as general data analysis techniques, healthcare terminology, and data modeling principles.
Browse courses on
Healthcare Data Analytics
Show steps
Show steps
Show steps
- Read the course syllabus and textbooks
- Attend the first few lectures and make notes
Practice data modeling exercises
Show steps
Gain hands-on experience creating and manipulating data models using industry-standard tools.
Browse courses on
Data Modeling
Show steps
Show steps
Show steps
- Complete the exercises provided in the course materials
- Find additional exercises online or in textbooks
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a study group
Show steps
Collaborate with peers to discuss course concepts, solve problems, and reinforce learning.
Show steps
Show steps
Show steps
- Find classmates who are interested in studying together
- Set regular meeting times and locations
- Prepare for each meeting by reviewing the course materials and completing any assigned exercises
- Actively participate in discussions and ask questions
Become a mentor to other students
Show steps
Share your knowledge and skills by mentoring other students in the course.
Show steps
Show steps
Show steps
- Contact your instructor or classmates to express your interest
- Match with a student who needs help
- Meet regularly to provide guidance and support
- Encourage your mentee to ask questions and seek clarification
Attend online workshops and webinars
Show steps
Supplement your learning with expert-led workshops and webinars on healthcare data analytics.
Show steps
Show steps
Show steps
- Search for online workshops and webinars
- Register for and attend the events
- Take notes and ask questions
- Apply what you learn to your own projects
Design a data analysis plan
Show steps
Develop a comprehensive plan outlining the steps involved in data analysis, from data collection to interpretation.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Identify the research question and objectives
- Choose appropriate data sources and methods
- Design a data collection strategy
- Develop a data analysis plan
- Write a data analysis plan document
Build a healthcare data analytics portfolio
Show steps
Create a portfolio of data analytics projects that demonstrate your skills and knowledge in healthcare.
Browse courses on
Data Analytics
Show steps
Show steps
Show steps
- Choose a project that interests you and is relevant to the field of healthcare
- Gather data and explore it
- Develop a data analysis plan
- Analyze the data and draw conclusions
- Create a presentation or report of your findings
- Reflect on your project and identify areas for improvement
Career center
Learners who complete Healthcare Data Models will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst is a kind of computer scientist that looks at data to extract patterns. Healthcare Data Analysts do this specifically in the medical field. They analyze a health system's records of patients, finances, and operations to find trends and help healthcare organizations make decisions. This course, Healthcare Data Models, teaches the foundational concepts of organizing and interpreting healthcare data. Graduates may find the course's information about common data models, data quality, and data measurement particularly valuable.
Statistician
Statistician
A Statistician collects and interprets data. A Healthcare Statistician works in the healthcare industry. They collect health-related data, analyze it, see if it is relevant, and work with doctors and researchers to help analyze and interpret the data. For example, they play an important role in designing clinical trials. Students of this course will gain insights into how to obtain healthcare-related data, model it, and analyze it.
Health Informatics Specialist
Health Informatics Specialist
A Health Informatics Specialist researches the use of information technologies in healthcare. They identify opportunities to improve the efficiency, effectiveness, and quality of healthcare systems through the use of technology. They may also teach healthcare professionals about new technologies and provide advice on how to use them. The Healthcare Data Models course helps build a strong foundation for this career, teaching about using and interpreting healthcare-related data for effective decision-making.
Business Analyst
Business Analyst
A Business Analyst studies the needs of a business and helps them find solutions to problems. In the healthcare industry, a Business Analyst works with other healthcare professionals to identify areas for improvement within a healthcare organization. They analyze data to find areas for improving business processes and efficiency, improving quality of service, and reducing costs. The course, Healthcare Data Models, can help teach these analysts how to understand and use data to improve healthcare.
Healthcare Administrator
Healthcare Administrator
A Healthcare Administrator plans, directs, and coordinates healthcare services. This course can be very useful for aspiring Healthcare Administrators. It teaches the fundamentals of organizing and interpreting healthcare data. This knowledge is valuable for healthcare administrators to make informed decisions and improve the overall efficiency and quality of healthcare services.
Data Engineer
Data Engineer
A Data Engineer designs, constructs, and maintains data architecture, systems, and infrastructure that store and process data. They build and maintain data pipelines, data warehouses, and data lakes. The Healthcare Data Models course may be helpful to Data Engineers hoping to work in healthcare. The course teaches the foundational concepts of organizing and interpreting healthcare-related data, which is key to designing and building healthcare-related data systems.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses advanced analytical techniques to help organizations make better decisions. They analyze data to find ways to improve efficiency, productivity, and quality. In healthcare, Operations Research Analysts work to improve healthcare delivery systems and patient outcomes. This course may be helpful to those in the healthcare industry with an interest in this career. It teaches healthcare data models, which will help them understand how healthcare data is organized and how it can be used to improve operations.
Medical Scientist
Medical Scientist
A Medical Scientist conducts research to understand the causes and mechanisms of disease. They apply scientific principles and methods to study human health and disease. The Healthcare Data Models course can be useful in giving Medical Scientists a solid foundation of healthcare-related data concepts. This knowledge will be helpful in their research endeavors.
Biostatistician
Biostatistician
A Biostatistician applies statistical methods to biological data. This course may be helpful for Biostatisticians, particularly those who wish to work in healthcare. It teaches about healthcare data models, data sources, and data types.
Healthcare Consultant
Healthcare Consultant
A Healthcare Consultant advises healthcare organizations on how to improve their operations. They may work with hospitals, clinics, and other healthcare providers to help them improve their efficiency, quality of care, and financial performance. The Healthcare Data Models course may be helpful to those seeking this career. It teaches the concepts of healthcare data modeling and data analysis, which can provide a solid knowledge base to advise clients.
Clinical Data Manager
Clinical Data Manager
A Clinical Data Manager plans, manages, and monitors the collection, processing, and analysis of clinical data. They work with investigators, research coordinators, and other members of the research team to ensure that data is collected and managed according to regulatory requirements. The Healthcare Data Models course can be helpful for aspiring Clinical Data Managers. It teaches about data models used in clinical research and clinical data management practices.
Public Health Analyst
Public Health Analyst
A Public Health Analyst collects, analyzes, and interprets data to identify and address public health issues. They may work with government agencies, non-profit organizations, or private companies to improve the health of communities. The Healthcare Data Models course may be helpful for those seeking this career. It teaches the concepts of healthcare data modeling and data analysis, which can provide a solid knowledge base to understand public health issues and how to address them.
Epidemiologist
Epidemiologist
An Epidemiologist investigates the distribution and patterns of health-related events and diseases in a population. They use this information to help prevent and control disease outbreaks. The Healthcare Data Models course may be helpful for aspiring Epidemiologists. It teaches the concepts of healthcare data modeling and data analysis, which can provide a strong foundation to understand the distribution and patterns of health-related events and diseases in a population.
Health Economist
Health Economist
A Health Economist applies economic principles to healthcare issues. They analyze the costs and benefits of different healthcare interventions and policies. This course may be helpful for aspiring Health Economists, particularly those who wish to work in healthcare. It teaches healthcare data models and the basics of healthcare data analysis.
Market Research Analyst
Market Research Analyst
A Market Research Analyst studies market trends and customer behavior to help businesses make better decisions. In healthcare, Market Research Analysts work to understand the needs of patients and healthcare providers. The Healthcare Data Models course can be useful to Market Research Analysts. It teaches the foundational concepts of organizing and interpreting healthcare data, which is valuable for understanding the market trends and customer behavior in the healthcare industry.
For more career information including salaries, visit:
OpenCourser.com/course/2y7p68/healthcare
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Healthcare Data Models.
Provides a comprehensive overview of healthcare data analytics, including data models, data mining, and machine learning techniques. Useful as a textbook or reference tool.
Covers the fundamentals of machine learning and its applications in healthcare, including predictive modeling, risk assessment, and personalized treatment. A useful textbook or reference for those interested in using machine learning for healthcare data analytics.
Provides a comprehensive overview of big data in healthcare, including topics such as big data storage, big data processing, and big data analytics. Useful for those involved in managing and analyzing big data in healthcare.
Provides a practical guide to clinical data analytics, including data collection, data cleaning, and data analysis methods. Useful for those involved in analyzing clinical data for research or quality improvement purposes.
Provides a comprehensive overview of healthcare data management and analytics, including data governance, data quality, and data integration. Useful as a textbook or reference tool for those involved in managing and analyzing healthcare data.
Save
Provides a comprehensive overview of healthcare data analytics, with a focus on the practical applications of data analytics in healthcare. It covers a wide range of topics, including data management, statistical analysis, machine learning, and artificial intelligence.
Covers the fundamentals of statistical methods and their applications in healthcare, including descriptive statistics, inferential statistics, and regression analysis. Useful for those involved in analyzing healthcare data for research or quality improvement purposes.
Provides a comprehensive overview of data visualization for healthcare, including topics such as data visualization techniques, data visualization tools, and data visualization best practices. Useful for those involved in communicating healthcare data to stakeholders.
Provides a gentle introduction to biomedical data science, covering topics such as data collection, data processing, and data analysis methods. Useful for those with no prior data science background.
Save
Provides a comprehensive overview of artificial intelligence (AI) in healthcare. It covers a wide range of topics, including the history of AI in healthcare, the different types of AI, and the ethical and legal considerations of AI in healthcare.
Provides a comprehensive overview of healthcare data analytics. It covers a wide range of topics, including the different types of healthcare data, the challenges of healthcare data analytics, and the different applications of data analytics in healthcare.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/2y7p68/healthcare
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Effort
4 weeks of study, 2-5 hours/week
Level
Intermediate
Via
Coursera
Institution
University of California, Davis
Instructor
Doug Berman
Language
English
Transcripts
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This course belongs to a
collection
called
Health Information Literacy for Data Analytics. It's comprised of four courses:
- Healthcare Data Models (viewing)
- Analytical Solutions to Common Healthcare Problems
- Healthcare Data Quality and Governance
- Healthcare Data Literacy
Good to know
Explores a relevant topic in healthcare data analytics and its impact on the industry
Develops valuable skills desired by healthcare industry employers, including data analysis and communication
Provides a strong overview of healthcare data models, enhancing foundational understanding
Emphasizes the importance of data quality and validation, fostering attention to detail and precision
May require familiarity with basic healthcare principles and terminology
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