Training activity information
Details
Devise the data analysis to answer a real-world clinical question
Type
Developmental training activity (DTA)
Evidence requirements
Evidence the activity has been undertaken by the trainee.
Reflection on the activity at one or more time points after the event including learning from the activity and/or areas of the trainees practice for development.
An action plan to implement learning and/or to address skills or knowledge gaps identified.
Considerations
- Appropriate methodology
- Design process
- “Good enough” solutions
Reflective practice guidance
The guidance below is provided to support reflection at different time points, providing you with questions to aid you to reflect for this training activity. They are provided for guidance and should not be considered as a mandatory checklist. Trainees should not be expected to provide answers to each of the guidance questions listed.
Before action
- What is the specific real-world clinical question? What data is available to address this question? What analytical approaches might be suitable?
- What will you learn about translating a clinical question into an analytical framework? How will you consider the clinical relevance of potential findings?
- Will you research similar clinical questions and how they have been analysed? Will you discuss the clinical context with relevant professionals?
- How do you feel about devising this data analysis? How does answering a clinical question differ from answering an operational question?
- Will there be an impact on clinical care as a result of this analysis? If so, how does this change your approach?
In action
- How are you translating the real-world clinical question into a specific analytical approach? What variables are you considering? What type of analysis (e.g., descriptive, comparative, predictive) are you using? What are the initial steps you are outlining for the data analysis?
- Are you finding it challenging to define the clinical question in a way that is amenable to data analysis? Are you identifying potential data sources that could provide insights? What are you learning about the process of bridging the gap between clinical needs and data analysis?
- If your initial analytical ideas seem insufficient to answer the clinical question, are you brainstorming alternative approaches? Are you refining the scope of your analysis based on the availability and nature of the data? Are you seeking clarification on the clinical question from relevant stakeholders?
On action
- What was the real-world clinical question you addressed? What data analysis approach did you devise? What were the key variables you considered? What type of analysis did you focus on (e.g., descriptive, comparative, predictive)?
- What did you learn about translating a clinical question into a data analysis plan? Did you face any difficulties in identifying relevant data or suitable analytical techniques? How did your immediate thinking during the task help you refine your analytical approach? How does this relate to the role of data science in addressing clinical needs? What are the important considerations when framing a clinical question in a way that can be answered by data analysis?
- How will you approach devising data analyses for clinical questions in the future? What aspects of clinical data or analytical techniques do you need to understand better? How can you collaborate effectively with clinical colleagues in this process? What are your next steps to develop your skills in devising data analyses for real-world clinical problems?
Beyond action
- Considering your increased exposure to clinical data and challenges, how would you refine the data analysis approach you initially devised for the clinical question? Have you worked on other real-world clinical questions since this training activity? How has your approach to translating clinical needs into analytical plans changed? Did discussions with clinicians or other healthcare professionals offer alternative perspectives on how data analysis could address the clinical question? Revisit your reflect-on-action notes. Has your understanding of the clinical question and the potential of data analysis to address it evolved?
- Has this exercise improved your ability to understand the data analysis requirements arising from real-world clinical problems? How has it contributed to your appreciation of the role of data science in addressing clinical needs and improving patient care? Has this training activity enhanced your ability to collaborate with clinicians to define answerable research questions? Has it influenced how you think about the practical challenges and ethical considerations of using clinical data for analysis?
- What skills in problem-solving, communication (with clinical stakeholders), and understanding clinical context did you develop through this training activity? What further learning will you undertake to deepen your understanding of clinical data and its applications in healthcare improvement? How will your ability to devise relevant data analyses contribute to your future role in informing clinical decision-making and healthcare policy?
Relevant learning outcomes
| # | Outcome |
|---|---|
| # 3 |
Outcome
Plan and execute the statistical analysis of data to answer questions relating to healthcare using appropriate methods with a clear and defensible rationale. |