Module manager: Dr Kate Absolom
Email: k.l.absolom@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2024/25
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 is an updated for YCHI5010M to reflect the inclusion of introduction of data science. Has been core for Health Informatics MSc and DTC in Computing. It retains some previous curriculum with the additional of research methods for Health Data Science.
This module is not approved as an Elective
This module is designed to introduce students to a modern conceptualisation of Health Informatics with Data Science. Students will be introduced to the central supporting role of Health Informatics and Health Data Science in the broad and complex activities involved in delivery quality evidence driven health care. This draws on the evidence base and the research methodologies supporting innovation and research.
- Introduce students to the broad and complex activities in healthcare and the central role of informatics and Health Data Science in supporting for example technology, systems, clinical decision making and patient self-monitoring.
- Introduce students to the uses of large scale existing data sources including the concepts of robustness of the data and potential generalisability.
- To introduce students to research methods used in evaluation
- Provide students with an overview of the types of research evidence and data with a focus on observational designs
- To explore the uses of health data in quality improvement
- To enable students to search for and critically evaluate evidence in complex health care environments
By the end of this module students should be able to:
1. Demonstrate a critical understanding of the contribution that health informatics can make to improving patient care
2. Describe and interpret informatics theory, concepts and practice.
3. Critically evaluate the usability of large routine health datasets
4. Articulate the potential biases within observational data
5. Demonstrate a critical understanding of the uses of routinely collected health data in quality improvement in care
6. Critically appraise published studies using large datasets addressing health care improvement challenges
• The basic principles of health informatics taking a critical approach to what it encompasses. Primarily within the English NHS but will consider approaches taken in other countries.
• Clinical encounters and the role of routinely collected health care data in individual patient care and quality improvement and for population based planning, audit and research at local, national and international level.
• An overview of the range of research study designs including, retrospective and prospective cohorts, cross-sectional and longitudinal studies, individual and aggregated data.
• An introduction to the evidence for diagnostic tests, information and decision making, including traditional evaluation approaches to tests used for screening and diagnosis (clinical data, biomarkers, imaging, sensors and devices) but also ‘precision medicine’ applications like risk stratification and the early detection of disease, AI.
• Observational designs, using non-randomized data for comparative purposes, confounding, natural experiments, propensity scores and instrumental variables.
• Descriptive uses of data, safety monitoring, patterns of disease and risk factors, population-level indicators used for service planning and commissioning purposes (e.g., frailty scores)
• The role of data standards; security and risk implications in health care
• Secondary research, searching and evidence synthesis
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Lecture | 10 | 2 | 20 |
| Practical | 2 | 1.5 | 3 |
| Seminar | 4 | 2 | 8 |
| Private study hours | 119 | ||
| Total Contact hours | 31 | ||
| Total hours (100hr per 10 credits) | 150 | ||
119 hours. Students will be expected to read and consolidate the materials from the classes, along with additional literature. This time will also be spent working on a group presentation and an independent piece of coursework.
Lectures and seminars will be interactive, including group discussion and problem-based exercises. There will be plenty of opportunity for rapid face-to-face feedback and clarification from the tutors during classes.
A draft 500 word outline of the written coursework will be submitted for formative assessment, so students will gain individual feedback directly applicable to their preparation for the summative work.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Literature Review | 3,000 words | 100 |
| Written Work | Formative 500 words outline plan including search strategy for summative | 0 |
| Total percentage (Assessment Coursework) | 100 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
The reading list is available from the Library website
Last updated: 29/04/2024
Errors, omissions, failed links etc should be notified to the Catalogue Team