We may earn an affiliate commission when you visit our partners.
Course image
Coursera logo

Healthcare Data Models

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.

Enroll now

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
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

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:
Save

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"

Career center

Learners who complete Healthcare Data Models will develop knowledge and skills that may be useful to these careers:
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.

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.
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.
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.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Healthcare Data Models.
Healthcare Data Quality and Governance
Most relevant
Analytics in Healthcare Management and Administration
Healthcare Analytics Essentials
Health Data and Analytics
HI-FIVE: Health Informatics For Innovation, Value &...
Cybersecurity in Healthcare (Hospitals & Care Centres)
Business Application of Machine Learning and Artificial...
Try It: Intro to Python
Using clinical health data for better healthcare
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser