Introduction to E-Learning Pathway for Data Analysts

1. Background

Welcome to SNOMED CT for Data Analysts! We hope you enjoy following this learning and learning about how to leverage the capabilities of SNOMED CT to achieve your clinical data analytics goals!

Why is SNOMED CT Useful for Clinical Data Analytics?

SNOMED CT is fundamentally designed around the meaning of clinical ideas, which we call ‘concepts’. This means that clinical data can be queried and analyzed based on its clinical meaning and the relationships between these meanings. Furthermore, because SNOMED CT provides concepts at different levels of detail, clinical data can be recorded at a granular level of detail (if required), and then aggregated or queried at various higher levels of clinical abstraction.

SNOMED CT also provides multilingual synonyms to refer to these clinical concepts. The concept centric approach ensures that equivalent queries (which use terms from different languages) all refer to the same clinical meanings.

Another important feature of SNOMED CT, which distinguishes it from statistical classifications (such as ICD) is that it uses a “polyhierarchy”. This means that each code can be grouped under more than one category, based on different aspects of its meaning. This enables SNOMED codes to be queried from different perspectives and aggregated in different ways.

One of the most significant reasons why SNOMED CT is so powerful for data analysis is that it uses formal Description Logic as the foundation for its clinical concept definitions. This means that we can leverage formal machine reasoning techniques to enable new relationships to be inferred from the clinical data.

Other reasons why SNOMED CT is useful for analyzing clinical data include:

• SNOMED CT is the most comprehensive clinical terminology in the world, and as such it provides a broad clinical coverage across a range of clinical disciplines, specialties and domains
• SNOMED CT is regularly updated which allows new clinical knowledge to be included and continual improvements to be made
• SNOMED CT provides robust versioning and retains a full history of all changes, to help manage queries over longitudinal health records that may span many years or decades
• SNOMED CT is an international terminology, so queries, subsets, rules and maps can be shared and reused between countries
• SNOMED CT has localization mechanisms that allow queries to be applied to data from different countries, dialects, regions and applications

What Types of Clinical Data Analytics does SNOMED CT Support?

SNOMED CT is designed to support the accurate and precise capture of clinical information at the point of care, and the subsequent meaning-based retrieval of this data. This allows SNOMED CT to support a wide range of analytics tasks, including: 

• Point of care reporting
• Patient summaries
• Clinical decision support
• Trend analysis
• Pharmacovigilance
• Clinical service and quality audits
• Predictive medicine
• Clinical research
• Semantic search

2. Purpose

The goal of the SNOMED CT for Data Analysts learning pathway is to provide a solid understanding of how the features and capabilities of SNOMED CT can help you to achieve your clinical data analytics objectives.

Please note that this learning pathway will NOT provide training on statistical analysis techniques. It will also NOT recommend specific clinical data analytics tools. Finally, it will NOT teach you how to develop software that implements data analytics techniques. If you would like to learn how to develop software to create data analytics tools, then please follow the SNOMED CT for Developers learning pathway.

The focus in this learning pathway is on teaching you how to apply the features of SNOMED CT to perform data analytics over clinical data.

3. Overview

SNOMED CT for Data Analysts has 4 main topics which are arranged into sections as follows:

• Introduction
  • The Introduction contains learning resources to help a data analyst get started with SNOMED CT. It provides relevant background to understand how SNOMED CT can be used to support effective and high quality data analysis.
  • Sections - Overview, Background, SNOMED CT and ICD
• SNOMED CT Features
  • SNOMED CT Features explains the key design features of SNOMED CT that may be useful to data analysts.
  • Sections - Design, Reference Sets, Computable Languages
• SNOMED CT Content
  • SNOMED CT Content explores the wide range of clinical concepts found in SNOMED CT, and describes the different defining relationships that can be used in queries. It also explains how SNOMED CT can be used within clinical information models.
  • Sections - Overview, Hierarchies, Terminology Binding
• Analytics
  
  • The Analytics topic explains different techniques for using SNOMED CT in clinical data analysis, and how these techniques can be applied to analytics tasks. It also explores a number of case studies in which SNOMED CT has been used to perform data analysis.
  • Sections - Overview, Case Studies, Mapping, Description Logic

For more information about each of the topics, please visit the relevant topic page and read the associated section descriptions (displayed by clicking the What is this section about? link).

4. Instructions

For each section in SNOMED CT for Data Analysts we have included a set of E-Learning presentations, and a list of links to related documents and resources. To expand the list, just click on the link that says 'Related Documents and Resources (click to show/hide)'.

When you have finished watching a presentation, a tick will appear in the progress box to the right of the presentation, which indicates that the presentation has been watched at least once. However, each presentation can be rewatched as many times as you like.

If the progress box is ticked, this may mean that you have already watched this presentation in one of our other courses or learning pathways.

Please note that all of the E-Learning presentations from our courses are available through the Presentation Library on the SNOMED CT E-Learning server.