Training activity information
Details
Apply diagnostic and prognostic algorithms with supervision from a consultant
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
- Diagnostic and therapeutic implications
- Local SOPs
- Internal quality control
- International, national and local policies and guidelines
- RCPath cancer datasets
- NICE guidance
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 are some key diagnostic and prognostic algorithms used in the assessment of the listed cancers?
- Are you familiar with the different types of data that may be included in diagnostic and prognostic algorithms (e.g., histological grade, stage, biomarker status)?
- Do you understand the purpose and limitations of using these algorithms?
- Are you aware of any specific algorithms that are routinely used in your department for the listed pathologies?
- How will this activity improve your ability to synthesise different pieces of information to arrive at a diagnosis or prognosis?
- What will you learn about the practical application of established guidelines and algorithms in real-world cases?
- How will you develop your understanding of the consultant’s role in guiding the application of these algorithms?
- Review relevant diagnostic and prognostic algorithms for the listed cancers (e.g., AJCC staging, grading systems, risk stratification tools).
- Discuss with your training officer specific cases where these algorithms have been applied and the outcomes.
- Consider potential challenges in applying algorithms to complex or unusual cases and think about how to approach these with your supervisor.
In action
- What specific clinical, histological, immunohistochemical, and molecular data are you inputting into the algorithm? Why are these data points crucial?
- What immediate steps are you taking as you progress through the algorithm? Are there any decision points where you need to pause and consider further information?
- Are you encountering any difficulties in applying the algorithm to the specific case? How are you adapting your approach?
- How does the output of the algorithm align with your initial understanding of the case? Are there any unexpected results that require further consideration?
On action
- What specific diagnostic or prognostic algorithms were applied?
- What data inputs were required for each algorithm (clinical, histological, molecular)?
- What were the outputs or classifications generated by the algorithms?
- How did the consultant guide you through the application of these algorithms?
- How do these algorithms integrate different types of data to aid in diagnosis and prognosis?
- What are the key decision points and criteria within these algorithms?
- What are the benefits and limitations of using diagnostic and prognostic algorithms?
- How did the algorithm outputs compare with the overall clinical picture of the cases?
- Which specific diagnostic and prognostic algorithms will you ensure you are familiar with for these cancers?
- What resources will you use to learn more about the principles and application of these algorithms?
- How will you integrate the use of algorithms into your future practice?
Beyond action
- How has your subsequent experience in requesting and interpreting immunohistochemistry and molecular tests informed your understanding of the practical application of diagnostic and prognostic algorithms you engaged with in this DTA?
- Reflecting on clinical experiences where you observed the entire patient pathway from diagnosis to treatment and follow-up, how has this holistic view influenced your understanding of the role of algorithms in guiding clinical decision-making, compared to your perspective during this DTA?
- How has this initial supervised application contributed to your increasing autonomy and confidence in applying these algorithms in your current practice?
- Have you encountered situations where you needed to adapt or deviate from standard algorithms based on specific patient circumstances? How does reflecting on this DTA inform your approach to such situations?
Relevant learning outcomes
| # | Outcome |
|---|---|
| # 4 |
Outcome
Apply diagnostic and prognostic algorithms. |