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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.

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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.
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Traffic lights

Read about what's good
what should give you pause
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

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Reviews summary

Overview of healthcare data models

Learners say this course provides an excellent high-level overview and clear explanations of healthcare data models and the data pipeline. It is particularly well-suited for beginners or professionals transitioning into healthcare data or non-technical healthcare staff. The coverage of key conceptual topics like data quality, normalization, and different data models is appreciated. However, some students note it is too basic for those with existing data background and lacks technical depth or hands-on practice, making it more theoretical than practical for building implementation skills. It effectively lays a conceptual foundation but is not a deep dive.
Introduces essential topics like data quality and models.
"I especially appreciated the module on data quality, which is crucial in this field."
"The course covers the main data models used..."
"Key data model types are introduced effectively."
"The module on data quality control was highly relevant."
Highly recommended for newcomers to the field.
"Highly recommend for beginners in healthcare data."
"Useful for absolute beginners..."
"...provides a great starting point for those entering the field."
"...well-explained for a non-technical audience or beginner."
Makes complex topics accessible and easy to follow.
"The explanations were clear and easy to follow, making complex topics accessible."
"...explained the concepts clearly without getting bogged down in technical jargon."
"It breaks down complex topics into digestible modules."
"The explanation of data normalization was clear."
Provides a strong conceptual introduction.
"This course provides an excellent high-level overview of healthcare data models and the data pipeline."
"A solid introduction to the subject... good for understanding the landscape."
"Provides a solid foundation."
"Exactly what I needed!... helped me understand the data side of things much better."
Focuses on theory, not practical application.
"It's more conceptual than technical... doesn't teach you how to actually implement or query these models using tools like SQL."
"The content is okay, but a bit too basic if you already have some background in data modeling or healthcare IT."
"It's extremely theoretical with no practical application or examples using real tools. If you're looking to actually work with healthcare data, this course won't teach you how."
"The lack of hands-on labs or technical exercises is a significant drawback for me; it's all theory."

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
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
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
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
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
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
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
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
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

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.
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.
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.
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.

Featured in The Course Notes

This course is mentioned in our blog, The Course Notes. Read one article that features Healthcare Data Models:

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.

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