Course Details
Contact(s):
for more information or to be notified when applications are open.
Brief Description
There are a limited number of fully funded places available for this course under the Reboot Skills Project. For further information please email linda.keane@ul.ie
Please ensure you enter the Module Code above when applying for this module. Applications without this cannot be processed. You may apply for more than one module under the same application.
|
Module Description |
Module Code |
NFQ Level |
ECTS Credits |
Start Date |
Fee |
|
Introduction to Real World Data in Cancer Clinical Research |
BM6053 |
9 |
9 |
TBC |
  €900 for EU and Non EU students |
The purpose of this module is to upskill professionals who interact, manage, curate or analyse cancer electronic health data and/or are engaged in cancer real world evidence research. Real-world data describes health data, collected outside of randomised controlled trials typically as part of routine clinical practice. If analysed appropriately, real world data can generate real-world evidence, which can offer insights into disease and the benefits and risks of therapeutic interventions as observed in a real-life environment. This module describes the types of data in a cancer patient’s electronic health record and their secondary use in research.
Learning Outcomes
On successful completion of this module, students will be able to:
- Critically assess secondary use of cancer data for research.
- Evaluate existing and emerging international clinical data standards for secondary use and analysis of cancer data, the use of vocabularies, ontologies and organisations that govern data standards.
- Critically evaluate research use of cancer health data, differentiating data use in clinical practice, emerging cancer clinical trial designs, and real-world evidence research.
- Recommend strategies and best practices in secure sharing data for secondary analysis.
- Conduct a comprehensive review of emerging literature on the secondary use of cancer patient healthcare imaging, genetic or genomics data and write a report that communicates these data and interprets the findings.
- Display a professional commitment to ethical data practice.
- Demonstrate an appreciation of the pace of technological and computational research advances in cancer and gain an insight into the potential risks and benefits of federated data sharing and analysis.
- Present a patient record as it might be presented to a molecular tumour board.
Assessment
There is no final exam for this module. You will be assessed through continuous skill-based assignments, provided by your lecturer and tutor.
Weekly Time Commitment
12 hours
Applicants must have a minimum Level 8 honours degree, at minimum second class honours (NFQ or other internationally recognised equivalent) in a clinical, healthcare, science or computing or related discipline, or a minimum of 5 years relevant professional experience in healthcare informatics or related setting.
Entry requirements are established to ensure the learner can engage with the course material and assessments, at a level suitable to their needs, and the academic requirements of the module. By applying to this micro-credential, you are confirming that you have reviewed and understand any such requirements, and that you meet the eligibility criteria for admission.
Successful completion of this module does not automatically qualify you for entry into a further award. All programme applicants must meet the entry requirements listed if applying for a further award.
€900 for EU and Non EU students