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By the end of the course, you will know how to apply common frameworks and key concepts in data analytics, systems theory and information governance.
The course starts by examining how healthcare data is collected and stored. It then goes on to explore how information management methods, machine learning and data visualisation are used in data analysis.
You will learn to leverage data analysis tools and techniques to inform better decision-making in healthcare.
What topics will you cover?
- What is healthcare data? Why is it important? What are the current challenges?
- How to address the unique data challenges facing healthcare.
- How can data impact healthcare innovation?
- How to develop a healthcare data proposal.
What will you achieve?
By the end of the course, you'll be able to...
- Explore healthcare data and understand key terminology and concepts.
- Identify key data challenges currently facing healthcare.
- Identify current trends and approaches in dealing with challenges and limitations related to healthcare data.
- Investigate how continual adjustments to data-centric health systems can be embedded within such systems to improve healthcare and health analytics.
- Assess the tension between competing interests and needs of stakeholders in relation to the analysis of healthcare data.
- Identify changes in medicine over the last 20 years.
- Assess the objectives of personalised medicine and the way data aggregation is impacting its development.
- Discuss the relationship between digital health and consumerisation of healthcare data.
- Develop a project proposal that identifies a problem, and address the key aims and objectives in solving the issue.