WM9M8-15 Big Data and Data Analysis for Healthcare
Introductory description
This module focuses on health data, its characteristics, and the different techniques available to enable clinical and operational data-driven decision making, and how to communicate data analysis outcomes to a range of different stakeholders. Healthcare is a data-driven activity to inform clinical practice, thus it is necessary for digital health professionals to have a sound knowledge of the health data landscape and of the various methodologies and tools available to analyse, interpret and visualise data. This module also covers the management, usage and accessibility of data relating to ethical, legal standards and regulatory guidelines to maintain trust in the use of health data and new methodologies such as Artificial Intelligence for all uses.
Module aims
To develop knowledge and skills about the concepts of data analysis and interpretation of quantitative data in healthcare, to address the basic ideas underlying statistical methods at an introductory level and to utilise big data knowledge and skills to empower students in their future careers
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
- Basic principles of statistics and statistical modelling.
- principles of data analysis and analytical models
- Big data and its role in healthcare
- Ethical and legal aspects related to data use in healthcare
- Data visualisation and interpretation
Learning outcomes
By the end of the module, students should be able to:
- Appraise the different types of data, basic descriptive statistical concepts, data visualisation techniques
- Appraise how data quality affects the analysis and leads to better decisions and future planning.
- Assess the different approaches used to store data and how these affect data accessibility and analyses.
- Appraise the role of data analysis and the four analytical models (descriptive, diagnostic, predictive and prescriptive) in managerial decision making for healthcare institutions
- Assess the ethical and legal aspects of the national and international regulatory guidelines to protect patient information
Indicative reading list
TBC
Subject specific skills
- Importance of data in healthcare and the different types of data
- How decisions are made based on data analysis
- The role of data in designing clinical decision support systems.
- Knowledge about the ethical and legal aspects and guidelines
Transferable skills
- Data retrieval
- Data analysis
- Data visualisation and interpretation
- Ethical and legal aspects related to data use in healthcare
Study time
| Type | Required |
|---|---|
| Seminars | 30 sessions of 1 hour (20%) |
| Private study | 60 hours (40%) |
| Assessment | 60 hours (40%) |
| Total | 150 hours |
Private study description
Guided trigger activities to support learning
Costs
No further costs have been identified for this module.
You must pass all assessment components to pass the module.
Assessment group B1
| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
| open book examination ( 4 hours) | 100% | 60 hours | No |
|
Data analysis interpretation and report |
|||
Feedback on assessment
written feedback on script and via assessment sheet on tabula
Courses
This module is Core for:
- MSc Digital Transformation for Healthcare