2022/23 Taught Postgraduate Module Catalogue

YCHI5083M Human Factors in Health Data Science

15 creditsClass Size: 40

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

Taught: 1 Mar to 30 Apr View Timetable

Year running 2022/23

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

Behind any dataset and using any digital health system, are people. They are responsible for designing systems, for entering data, for interpreting it and acting on the information. This module uses concepts and research from a range of disciplines to show why data is never just numbers and that health data science needs to be about respecting limitations as well as exploiting opportunities. The module will explore safety and usability, as well as stakeholder involvement and behaviour change.

Objectives

The purpose of the module is to:
• Introduce students to the key principles of human factors as applied to health care systems and health data science, and the varied roles of different stakeholders.
• Enable students to understand the connections between usability, safety and error in data and systems.
• Enable students to critically appraise behaviour change interventions and understand the function of processes and workarounds.

Learning outcomes
By the end of this module students should be able to:
1. Describe the various ways bias, gaps and errors may be introduced into data, and consider how these might be mitigated.
2. Articulate how designing for safety can mitigate errors in digital health systems; critically appraise how and why errors occur and how frameworks may be applied to aid understanding.
3. Describe how usability design concepts can affect the effective use of systems and data, and critically evaluate system design based on these principles.
4. Critically appraise interventions for behaviour change and the ways they may be evaluated.
5. Critically analyse pathways and workflow, including workarounds, and consider them as candidates for quality improvement.
6. Explain how different stakeholders (e.g. patients, carers, clinical and non-clinical staff) may be included in the design and implementation of systems or interventions.

Syllabus

- Data provenance, scope, biases, limitations.
- Missing data and selective supply of data in audits, QA, PROMS, surveys, social media.
- Clinical informatics, coding and classification, data quality, re-use of data.
- Professionals, patients and the public as suppliers, processors and users of health data.
- Usability, user-centred design / co-design, presentation quality vs interpretability and evidence.
- Patient safety, risk and error, frameworks for understanding.
- Pathways,(patients) workflow ( staff) and workarounds, process improvements.
- Behaviour change: symptom checkers, mobile health and lifestyle modification.
- Personalised care and decision support.
- Stakeholder involvement, policy development, strategic planning and quality improvement.

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	10	2.00	20.00
Practical	1	2.00	2.00
Seminar	6	1.00	6.00
Private study hours			122.00
Total Contact hours			28.00
Total hours (100hr per 10 credits)			150.00

Private study

122 hours private study. 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 an independent piece of coursework.

Opportunities for Formative Feedback

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 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.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Essay	2,500 words	100.00
Written Work	Formative, 500 words outline	0.00
Total percentage (Assessment Coursework)		100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

There is no reading list for this module

Last updated: 29/04/2022 15:42:20

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