2024/25 Taught Postgraduate Module Catalogue

YCHI5082M Foundations of Health Data

15 creditsClass Size: 40

Module manager: Ruth Evans
Email: r.p.evans@leeds.ac.uk

Taught: 01 Oct to 31 Dec View Timetable

Year running 2024/25

Pre-requisite qualifications

First degree in a relevant subject e.g. Social Sciences, STEMM, Nursing (or equivalent) 2:1 OR previous work experience (minimum 2 years) of handling and/or analysing data

IELTS 7 – minimum of 6.5 in each component

This module is not approved as an Elective

Module summary

This module introduces students to what, when, how, why and by whom health data is collected, processed and shared in the health domain. The different categories of health data (e.g. prescriptions, procedures, referrals) and dimensions of health (e.g. patients and time) will be described. Students will then be introduced to some of the key data sources and data flows in the health domain and will consider how the provenance of data can impact data quality and subsequent usage. Data standards will be described as a mechanism to achieve syntactic and semantic interoperability in the health domain.

Objectives

The purpose of this module is to:
• Give students an understanding of the heterogeneity, scale and complexity of data that is collected, processed and shared in the health domain
• Provide students with knowledge of how data standards can be used to reduce ambiguity and increase interoperability in the health domain
• Equip students with an understanding of data provenance and data quality, and how they impact on subsequent usage

Learning outcomes
By the end of the module, students will be able to:
1. Articulate the different categories and dimensions of health data
2. Demonstrate a sophisticated understanding of the key data sources and flows in the health domain
3. Critically analyse the provenance of health data and evaluate the potential impact on data quality
4. Demonstrate a sophisticated understanding of the different ways in which health data is used to drive decisions in the health domain
5. Critically evaluate the role of data standards in syntactic and semantic interoperability
6. Critically interpret key data standards that are used to represent health data

Syllabus

This module covers the following topic areas:
• Categories and dimensions of health data
• Data flows in the health domain
• Provenance of health data
• Applications of health data
• Data standards and interoperability

Teaching methods

Delivery type	Number	Length hours	Student hours
Group learning	2	2.00	4.00
Lecture	13	2.00	26.00
Private study hours			120.00
Total Contact hours			30.00
Total hours (100hr per 10 credits)			150.00

Private study

120 hours private study.

Opportunities for Formative Feedback

Group presentations will be prepared and delivered by students as part of the module to provide an opportunity for ongoing feedback from teaching staff and peers.
Students will undertake a group learning task on a selected topic which will require the development and delivery of a presentation to peers at the end of the module.
Students will peer-review the presentations of other groups and share comments. Teaching staff will also provide feedback comments to each group.
Students will submit a 500 word outline plan of the summative assessment work for written feedback.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Report	Project report. 3,000 words	100.00
Written Work	500 word plan for formative feedback	0.00
Total percentage (Assessment Coursework)		100.00

Students will be assessed by writing a 3,000 word report on a real-world health data scenario. For example, students are provided with a scenario involving data captured by a clinician in General Practice. Students are then required to map the flow of that data between different organisations, including the different purposes for which it is processed and the standards that are used in its representation, and to identify potential for improvements.

Reading list

There is no reading list for this module

Last updated: 09/05/2024 11:42:15

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