Digital Health Principles

Learning Outcomes

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

• Identify and utilise key types of health data.
• Explain basic processes relating to data analytics and modeling;
• Explain and justify how data is collected, stored and responsibly shared in and between healthcare settings;
• Critique and compare data science pipelines;

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

• How those theories and techniques impact the quality of the data and how it should be used
• Key qualitative and quantitative research methods used in the study of digital health care;
• The drivers, enablers, barriers and challenges to digital health innovation
• User-focused development, meaningful evaluation and successful implementation of digital health tools;

Transferable and Generic Skills

Having successfully completed this module you will be able to:

• Present and interpret data to/for a non-technical audience.

The course will introduce students to the standards, theories and technologies in digital health. This module will cover how international healthcare Interoperability data standards can aid textual, image, and sensor analytics pipelines from data preparation to data processing, analysis and visualisation.

The course will cover the following:

Introduction to digital health

* Understanding the healthcare ecosystem, including ethics data protection & privacy

* Digital health drivers: data standards

* Digital health enablers, barriers and challenges

Overview of data standards in use for health data

* How do data standards work?

* How data standards are used in healthcare?

Data management

* Data types and formats

* Documentation and metadata

* Data storage and sharing

* Data principles & security

* Data management architectures

Data collection& Data sharing

* An introduction to mixed methods in health sciences

* Passive data collection: sensors for remote health monitoring

* Clinical unstructured data versus Clinical structured data

Data analytics essentials

* Overview of data-driven pipelines

* Practical Statistics

* Data visualisation

Application scenarios and state-of-the-art

* Using data for improvement: how to test a change that is implemented?

Teaching and learning methods

Lectures and Tutorials

Summative

This is how we’ll formally assess what you have learned in this module.