Module information
Module details
- Title
- Digital Health Tools and Clinical Decision Making
- Type
- Specialist
- Module code
- S-HI-S4
- Credits
- 10
- Phase
- 3
- Requirement
- Compulsory
Aim of this module
The aim of this module is to introduce trainees to how patient data and clinical knowledge is used to inform decision-making. Trainees will learn about the different forms of healthcare knowledge, how they are defined and represented, and the design and evaluation of decision support systems.
Work-based content
Training activities
| # | Learning outcome | Training activity | Type | Action |
|---|---|---|---|---|
| # 1 | Learning outcome 1,2,4 |
Training activities
Create a proposal for a clinical decision support tool and assess the benefits and risks of the proposed tool |
Type DTA | Action View |
| # 2 | Learning outcome 2,3 |
Training activities
Appraise current regulations covering software as a medical device (SaMD) and reflect on how these are used to assure patient safety |
Type DTA | Action View |
| # 3 | Learning outcome 1,2 |
Training activities
Review a digital health tool in use in the local healthcare organisation and map the data architecture underpinning it |
Type DTA | Action View |
| # 4 | Learning outcome 4 |
Training activities
Develop a simple prototype decision support tool using an evidence-based medicine approach |
Type DTA | Action View |
| # 5 | Learning outcome 3 |
Training activities
Appraise the regulations concerning the collection and ownership of data in digital health tools used by patients and clinicians |
Type DTA | Action View |
| # 6 | Learning outcome 1,2 |
Training activities
Summarise a range of digital health tools intended for patient use providing an assessment of usefulness and provide a recommendation for applicability to a specific workflow |
Type DTA | Action View |
| # 7 | Learning outcome 1,2 |
Training activities
Compare a decision support tool to a more traditional clinical decision-making approach, highlighting the benefits of the tool to clinicians and patients |
Type DTA | Action View |
| # 8 | Learning outcome 1,2,3 |
Training activities
Produce a one-page briefing on decision support tools for the department |
Type DTA | Action View |
| # 9 | Learning outcome 1,2 |
Training activities
Draft a business case for a decision support tool to replace an existing method |
Type DTA | Action View |
Assessments
Complete 2 Case-Based Discussions
Complete 2 DOPS or OCEs
Direct Observation of Practical Skills Titles
- Assemble a simple decision support tool.
Observed Clinical Event Titles
- Present a proposal for a decision support tool to an audience of peers.
- Discuss with a clinician the pros/cons of decision support tools compared to existing decision-making methodology.
- Present an appraisal/business case for deploying a decision support tool in a clinical workflow.
Learning outcomes
| # | Learning outcome |
|---|---|
| 1 | Describe the purpose and function of Decision Support Tools in healthcare. |
| 2 | Appraise the risk and benefits of using Decision Support Tools in clinical practice. |
| 3 | Apply the legislation and regulations applicable to Decision Support Tools. |
| 4 | Design a simple Decision Support Tool to solve a clinical problem. |
Clinical experiences
Clinical experiences help you to develop insight into your practice and a greater understanding of your specialty's impact on patient care. Clinical experiences should be included in your training plan and you may be asked to help organise your experiences. Reflections and observations from your experiences may help you to advance your practice and can be used to develop evidence to demonstrate your awareness and appreciation of your specialty.
Activities
- Observe the application of a decision support tool in the clinical environment.
- Attend a steering/project group meeting for the implementation of a new clinical technology/tool.
- Follow the data flow underpinning a decision support tool from the capture of the input data to how the tool output reaches clinicians. Consider the delays, risks, or gaps that are present within the information chain.
Academic content (MSc in Clinical Science)
Important information
The academic parts of this module will be detailed and communicated to you by your university. Please contact them if you have questions regarding this module and its assessments. The module titles in your MSc may not be exactly identical to the work-based modules shown in the e-portfolio. Your modules will be aligned, however, to ensure that your academic and work-based learning are complimentary.
Learning outcomes
On successful completion of this module the trainee will be able to:
- Critically evaluate the types of clinical decision support, including their strengths and weaknesses and areas where each might be applied.
- Assess the application of clinical decision support to benefit individuals and/or populations, including real-world examples.
- Demonstrate a practical understanding of how knowledge is transformed into a clinical decision support tool.
- Critically evaluate strategies for the evaluation of digital health and decision support tools.
- Discuss and apply frameworks for successful digital health tool adoption.
Indicative content
- Digital adoption and usage
- Factors to consider including usage of frameworks such as NASSS
- Requirement for decision support, susceptibility for bias and error
- Knowledge generation, acquisition and modelling tools
- Computable knowledge
- Personalised medicine
- Pharmacogenomics
- The role of decision support tools in genomics bioinformatics, including practical considerations of this
- Computer aided diagnosis in imaging
- Barriers to implementation
- Automation bias
- Bias within datasets and how these propagate into decision support
- Applicability of guidance