Course Details

Course Code(s):
BM6053
Available:
Part-Time
Intake:
Summer
Course Start Date:
23rd June 2024
Duration:
6 Weeks
Award:
University Certificate of Study
Faculty: Education and Health Sciences
Course Type: Professional/Flexible
Fees: For Information on Fees, see section below.
Application Deadline:

Contact(s):

Name: Prof Aedin Culhane
Email: aedin.culhane@ul.ie
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Brief Description

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

23rd June 2024

  €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:

  • Recommend standards for interoperability and secondary use of data in the cancer healthcare record
  • Explain why a common data model systems facilitates observational studies
  • Critically evaluate data quality of observational health data when framing a research question
  • Create and validate software to standardise raw health data to a common data model with standardised terminologies and ontologies
  • Evaluate software to query, map fields, construct concept sets, and standards for genetic and genomic data
  • Defend that software adheres to open-source software community best practice, and facilitates reproducible secondary data research.
  • Effectively and respectively participate in multidisciplinary research teams that process healthcare data for secondary use
  • Display commitment to ethical and rigorous standards in secondary use of healthcare data.
  • Design and produce an software that harmonises health data to a common data model and enables secondary data analysis

    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 

    15 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

    Please click here for information on funding and scholarships.