EdX

Health Informatics: Data and Interoperability Standards (edX)

Health Informatics: Data and Interoperability Standards (edX)

The key standards for representing and sharing healthcare data. Once electronic health records and other clinical systems used in patient care are digital, the focus turns to how this health information can be represented and shared using standards.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

Developing standards that are both sufficiently comprehensive and also implementable in practice is one of the long-standing health informatics challenges in part because of the complexity of the human body and the resultant complexity of patient care. We discuss data and data sharing (interoperability) standards separately but they are inevitably intertwined since the information being shared using interoperability standards is often represented using data standards.
This course is part of the Health Informatics on FHIR Professional Certificate program.

What you'll learn

  • Working familiarity with the major health care data standards
  • Awareness of the web-based tools for accessing the data standards
  • HL7 as the global health care interoperability standards organization
  • HL7 interoperability standards history
  • The HL7 interoperability standards that preceded FHIR
  • The FHIR interoperability standard
  • The SMART on FHIR EHR connected app platform
  • Familiarity with web-based tools for learning and utilizing FHIR and SMART on FHIR

Course Syllabus

Lesson 1 - Data Standards
1.1 - Introduction
1.2 - Why Standards?
1.3 - Standards Evolution
1.4 - Technology Evolution
1.5 - Key Data Standards
1.6 - International Classification of Disease (ICD)
1.7 - Current Procedural Technology (CPT)
1.8 - Logical Observation Identifiers Names and Codes (LOINC)
1.9 - National Drug Codes (NDC)
1.10 - RxNorm
1.11 - The Systemized Nomenclature of Medicine (SNOMED)
1.12 Data Standards Recap
Data Standards Activities
ICD
CPT
LOINC
NDC
RxNorm
SNOMED CT

Lesson 2- Pre-FHIR Interoperability Standards
2.1 - Introduction
2.2 - HL7's Evolution
2.3 - HL7 V2 versus V3
2.4 - Reference Implementation Model (RIM)
2.5 - RIM and FHIR
2.6 - Clinical Documentation Architecture (CCD/CCDA) Uses RIM
2.7 - CCDA Templates
2.8 - Clinical Decision Support (CDS)
2.9 - Homer Warner's HELP System
2.10 - AI Comes to Medicine
2.11 - Arden Syntax: A Standard for Medical Logic
2.12 - Arden Explained

Lesson 3- The HL7 FHIR Interoperability Standard
3.1 - The Origins of FHIR
3.2 - Grahame's Philosophy
3.3 - FHIR Resources
3.4 - FHIR Resource Representations
3.5 - FHIR Resource Examples
3.6 - FHIR Resource IDs
3.7 - Enabling Existing Systems
3.8 - FHIR API
3.9 - FHIRPath
3.10 - FHIR Conformance Modules
3.11 - The Argonaut Project
3.12 - Dr. Charles Jaffe Interview
3.13 - Grahame Grieve Interview
3.14 - FHIR Recap

Lesson 4 - SMART a Universal Health App platform
4.1 - A Grand Challenge
4.2 - SMART on FHIR Overview
4.3 - OAuth2
4.4 - Scopes and Permissions
4.5 - OpenID Connect
4.6 - SMART App Authorization
4.7 - SMART Backend Services
4.8 - CDS Hooks
4.9 - SMART Genomics
4.10 - Ken Mandl Interview
4.11 - Josh Mandel Interview
4.12 - Cerner's Kevin Shekelton Interview
4.13 - RIMIDI's Dr. Lucie Ide Interview

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

AI in Healthcare Capstone (Coursera) Coursera
Stanford University

AI in Healthcare Capstone (Coursera)

This capstone project takes you on a guided tour exploring all the concepts we have covered in the different classes up till now. We have organized this experience around the journey of a patient who develops some respiratory symptoms and given the concerns around COVID19 seeks care with a primary care provider. We will follow the patient's journey from the lens of the data that are created at each encounter, which will bring us to a unique de-identified dataset created specially for this specialization. The data set spans EHR as well as image data and using this dataset, we will build models that enable risk-stratification decisions for our patient.

Aug 31st 2026
5-12 Weeks
Healthcare Data Security, Privacy, and Compliance (Coursera) Coursera
Johns Hopkins University

Healthcare Data Security, Privacy, and Compliance (Coursera)

In the final course of the Healthcare IT Support program, we will focus on the types of healthcare data that you need to be aware, complexities of security and privacy within healthcare, and issues related to compliance and reporting. As a health IT support specialist, you’ll be exposed to different types of data sources and data elements that are utilized in healthcare. It’s important for you to understand the basic language of healthcare data and for you to recognize the sensitive nature of protected health information (PHI). Maintaining data privacy and security is everyone’s responsibility, including IT support staff!

Aug 31st 2026
4 Weeks
Health Informatics: The Cutting Edge (edX) EdX
Georgia Institute of Technology,GTx

Health Informatics: The Cutting Edge (edX)

Some of the key focus areas for health informatics research and development. Adopting digital health records and sharing the data they contain is a critical step forward. However, since successful management of chronic disease must involve patients, using informatics tools and systems to engage them is now a major area of focus for academic and industry research and development.

No sessions available
5-12 Weeks
Dynamical Modeling Methods for Systems Biology (Coursera) Coursera
Icahn School of Medicine at Mount Sinai

Dynamical Modeling Methods for Systems Biology (Coursera)

An introduction to dynamical modeling techniques used in contemporary Systems Biology research. We take a case-based approach to teach contemporary mathematical modeling techniques. The course is appropriate for advanced undergraduates and beginning graduate students. Lectures provide biological background and describe the development of both classical mathematical models and more recent representations of biological processes. The course will be useful for students who plan to use experimental techniques as their approach in the laboratory and employ computational modeling as a tool to draw deeper understanding of experiments.

Sep 7th 2026
5-12 Weeks
The Data Science of Health Informatics (Coursera) Coursera
Johns Hopkins University

The Data Science of Health Informatics (Coursera)

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).

Aug 24th 2026
4 Weeks
Using Data for Healthcare Improvement (Coursera) Coursera
Imperial College London

Using Data for Healthcare Improvement (Coursera)

In this course, you will learn about the importance of measuring the quality of care and health outcomes in order to determine whether Quality Improvement(QI ) initiatives have achieved their aims. You will learn about how data is utilised to identify areas of improvement and the importance of using both quantitative and qualitative data in evaluating change. You will learn about the specific methods appropriate for improvement as distinct from methods more suited to research, including how to design measurement schemes suitable for improvement initiatives

Aug 31st 2026
4 Weeks
Analytical Solutions to Common Healthcare Problems (Coursera) Coursera
University of California, Davis

Analytical Solutions to Common Healthcare Problems (Coursera)

In this course, we’re going to go over analytical solutions to common healthcare problems. I will review these business problems and you’ll build out various data structures to organize your data. We’ll then explore ways to group data and categorize medical codes into analytical categories. You will then be able to extract, transform, and load data into data structures required for solving medical problems and be able to also harmonize data from multiple sources.

Aug 31st 2026
4 Weeks
Designing Engaging Dashboards for Healthcare Analytics (Coursera) Coursera
Northeastern University

Designing Engaging Dashboards for Healthcare Analytics (Coursera)

Introduces processes and design principles for creating meaningful displays of information that support effective business decision-making. Studies how to collect and process data; create visualizations (both static and interactive); and use them to provide insight into a problem, situation, or opportunity. Introduces methods to critique visualizations along with ways to answer the elusive question: “What makes a visualization effective?” Discusses the challenges of making data understandable across a wide range of audiences.

Aug 31st 2026
4 Weeks
Leading Change in Health Informatics (Coursera) Coursera
Johns Hopkins University

Leading Change in Health Informatics (Coursera)

Do you dream of being a CMIO or a Senior Director of Clinical Informatics? If you are aiming to rise up in the ranks in your health system or looking to pivot your career in the direction of big data and health IT, this course is made for you. You'll hear from experts at Johns Hopkins about their experiences harnessing the power of big data in healthcare, improving EHR adoption, and separating out the hope vs hype when it comes to digital medicine.

Aug 31st 2026
4 Weeks