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Applied Clinical Data Analytics (MSc)
Course Overview
The taught postgraduate course in Applied Clinical Data Analytics employs a unique and innovative spiral curriculum, designed specifically for training healthcare professionals in analysis of healthcare data. Domain experts in Clinical Data Analytics from the College of Medicine, Nursing and Health Sciences will deliver the program. Assignments are all real-world examples of clinical research including clinical trials, systematic reviews, observational research, and data from administrative clinical datasets.
- The course is designed to train healthcare workers without a background in data analytics, statistics, or computer programming, to analyse and interpret healthcare data.
- Applies research and data analytics knowledge to clinical and health data to effectively answer research questions.
- We will teach students to understand and learn how to apply traditional statistical techniques and machine learning by completing weekly assignments and an end of year thesis.
- Students will learn data import, cleaning, exploration and analysis using the R programming language and R packages for data analysis, machine learning and source control using GitHub.
- We will teach research methodology and appropriate statistical analysis using R for randomised controlled trials, systematic reviews, case control studies and prospective cohort studies.
The Applied Clinical Data Analytics Masters was a 2024 finalist in the Irish Healthcare Centre Awards in Education, Learning & Development. This recognition is a testament to the hard work, dedication, and innovative spirit of every member of our team. Being named a finalist reaffirms our commitment to excellence in training healthcare professionals in the analysis of healthcare data.
Pictured Left to Right: Honor Griffin, Dr. Alberto Alverez-Iglesias, Dr. Conor Judge, Dr. Sonja Khan, Dr. Finn Krewer.
Applications and Selections
Course applications are then made online via the University of Galway Postgraduate Applications System.
Who Teaches this Course
1. Spotlight on Staff
Introducing some of the teaching staff of the Applied Clinical Data Analytics Masters programme: https://stories.universityofgalway.ie/introducing-our-teaching-team-acda/index.html
The Future of AI in Medicine
AI has massive potential to revolutionise and better medical care. However, it is not without its risks. In this TEDx Talk Dr Conor Judge,Co-Director & Senior Lecturer, Applied Clinical Data Analytics, and Consultant Nephrologist at Saolta University Health Care Group highlights what is needed in order to implement multimodal AI safely into the healthcare system.
View the Ted Talk here
2. A message from Co-Directors
Dr Conor Judge and Dr Sonja Khan and Team;
The role of clinical health data has become increasingly more important, offering insight into patient care, operational efficiency, and clinical research. Through this postgraduate taught Master’s programme we will equip healthcare professionals with health data analytics and research methodology skills to navigate this evolving landscape with confidence and knowledge. Students will learn how to ask and answer a research question using health data, code using the R programming language, the fundamentals of research methodology, an applied understanding of medical statistics, and how to create publication ready tables and figures. We are looking forward to welcoming our second student cohort in September 2024, the team are committed to fostering an inclusive and supportive learning environment.
3. Healthcare Centre Awards Finalist 2024
The Applied Clinical Data Analytics Masters was a 2024 finalist in the Irish Healthcare Centre Awards in Education, Learning & Development. This recognition is a testament to the hard work, dedication, and innovative spirit of every member of our team. Being named a finalist reaffirms our commitment to excellence in training healthcare professionals in the analysis of healthcare data.
Pictured Left to Right: Honor Griffin, Dr. Alberto Alverez-Iglesias, Dr. Conor Judge, Dr. Sonja Khan, Dr. Finn Krewer
Requirements and Assessment
Assessment is via a combination of continuous assignments (70%) and written exams (30%), that will be 100% computer-based assessment.
Key Facts
Entry Requirements
Students must have completed one of the following:
- An undergraduate degree in Nursing, Pharmacy, Physiotherapy, Medicine.
- Another healthcare-related undergraduate degree with a minimum of 2nd Class Honours.
- A biomedical related undergraduate degree with a minimum of 2nd Class Honours.
Applicants from non-healthcare related degrees will be considered on a case-by-case basis at the discretion of the coordinators (minimum requirement of 2nd Class Honours). Applicants with significant relevant experience will also be considered.
For applicants where English is a second language, we adhere to University of Galway guidelines, requiring IELTS scores of 6.5, TOEFL scores of 88, and/or Pearson PTE scores of 61, with no less than 5.5 in any component. The Duolingo test score requirement is 110 overall, with no less than 110 in any one component, and valid for two years.
Applicants who do not meet the primary entry criteria as described above will be declined entry into the program. The remaining applicants will be reviewed in closer detail, with significant weight placed on: A) The applicant’s essay describing their motivation for applying to this course and their career aspirations following the successful completion of the MSc. B) The applicant’s previous academic performance. C) The applicant’s referee’s comments.
*Or equivalent international qualification
Additional Requirements
Recognition of Prior Learning (RPL)
Duration
1 year, full-time (12 months); 2 years, part-time (24 months).
Next start date
September 2025
A Level Grades ()
Average intake
15
QQI/FET FETAC Entry Routes
Closing Date
Please view the offer rounds website.
NFQ level
Mode of study
ECTS weighting
90
Award
CAO
Course code
ACA1; ACA2
Course Outline
University of Galway have launched a graduate course in Applied Clinical Data Analytics that employs a unique and innovative spiral curriculum, designed specifically for training healthcare professionals in analysis of clinical data.
This programme is delivered by domain experts in Clinical Data Analytics from primarily within the School of Medicine and wider College of Medicine, Nursing and Health Science. Working within a dynamic active learning environment on clinical data will facilitate the development of profession appropriate, individual, collective and inter-professional data skills. Assignments are all real-world examples of clinical research including clinical trials, systematic reviews, observational research, and data from administrative clinical datasets.
Full-time students must complete six core modules (Figure 1) across semester 1 and 2 worth 60 ECTS. Students are also required to complete a Thesis project (30 ECTS) split into two parts. Part-time students complete this program over 2 years, completing 40 ECTS in year 1 and 50 ECTS in year 2 (Figure 2).
Range of Teaching/Formal Learning:
Tutorial-based teaching, flipped classroom, problem based learning, real life case studies will be applied and students will learn by applying statistical tools to work through data sets.
Research project:
Self-directed research project with continuous supervision and feedback.
Applied Clinical Data Analytics - Course Handbook - 2024-2025
Figure 2—Term Overview for MSc Applied Clinical Data Analytics (part-time)
Why Choose This Course?
Career Opportunities
There are various career paths in healthcare, research, and technology sectors. These roles often require a combination of skills in data analysis, and proficiency in relevant tools and technologies such as statistical software, database management systems, and programming languages like R that is taught on the Applied Clinical Data Analytics Masters.
Additionally, staying updated with advancements in healthcare regulations and technologies is crucial for success in these careers.
Here are some roles aligned to the Masters:
- Clinical Data Analyst: They analyse healthcare data to improve patient care, streamline operations, and support decision-making processes within clinical settings.
- Healthcare Data Scientist: Leveraging advanced statistical and computational techniques, they analyse complex healthcare data to derive insights, predict trends, and develop data-driven solutions for healthcare challenges.
- Clinical Informatics Specialist: They focus on integrating healthcare data with information technology systems to improve the efficiency and quality of healthcare delivery.
- Clinical Research Coordinator: Responsible for managing and analysing data collected during clinical trials, ensuring compliance with regulatory requirements and ethical standards.
- Epidemiologist: They investigate patterns and causes of diseases within populations, utilizing clinical data analytics to identify risk factors, track disease outbreaks, and inform public health interventions.
- Healthcare Quality Improvement Specialist: They use data analytics to monitor and evaluate the quality of healthcare services, identify areas for improvement, and implement strategies to enhance patient safety and satisfaction.
- Healthcare IT Project Manager: They oversee the implementation of data analytics projects, ensuring that they meet the needs of healthcare stakeholders while adhering to budget and timeline constraints.
The Masters also aims to enhance the current work of Healthcare professionals to become proficient clinical data analyst.
Here are a few highlights of what you can expect from our programme:
- Cutting-edge Curriculum: Our curriculum is crafted in collaboration with industry experts to ensure its relevance and effectiveness. You'll have the opportunity to explore advanced topics in clinical data analytics, gaining a deep understanding of how data-driven insights can enhance patient care.
- Expert Team: Learn from accomplished clinical staff who bring a wealth of experience in both academia and healthcare. They are dedicated to providing guidance as you navigate the programme.
- Hands-On Experience: Embrace practical learning through real-world case studies and projects, allowing you to apply your newfound knowledge in meaningful ways.
- Networking Opportunities: Connect with a diverse community of professionals, fostering valuable relationships that extend beyond the classroom. Our program provides a platform for collaboration and knowledge exchange.
- If you have any specific questions or would like to discuss your academic and professional goals in more detail, please feel free to reach out. We are here to support you on your journey to becoming a proficient clinical data analyst.
Fellowship opportunities:
The programme was able to offer two student fellowships for 2024. The aim of the fellowship is to provide students a unique opportunity to get hands-on experience in Applied Clinical Data Analysis in the Clinical Research Facility, Galway. The fellowship will provide a stipend for its duration, for a maximum duration of 6 months.
Who are these fellowship for?
- Students undertaking a full-time Masters in Applied Clinical Data Analytics
- High-achieving, suitably qualified and dynamic individuals, with drive and passion, who want to obtain necessary skills and knowledge of data analysis in the Clinical trials environment.
Applications open during the Academic year and the Fellowships will run from March- August.
Who’s Suited to This Course
Learning Outcomes
Transferable Skills Employers Value
Work Placement
Study Abroad
Related Student Organisations
Course Fees
Fees: EU
Fees: Tuition
Fees: Student levy
Fees: Non EU
For 25/26 entrants, where the course duration is greater than 1 year, there is an inflationary increase approved of 3.4% per annum for continuing years fees.
Postgraduate students in receipt of a SUSI grant – please note an F4 grant is where SUSI will pay €4,000 towards your tuition (2025/26). You will be liable for the remainder of the total fee. A P1 grant is where SUSI will pay tuition up to a maximum of €6,270. SUSI will not cover the student levy of €140.
Note to non-EU students: learn about the 24-month Stayback Visa here.
Find out More
E: clinicaldataanalytics@universityofgalway.ie
Programme directors
Dr Conor Judge,
School of Medicine
E: conor.judge@universityofgalway.ie
Dr Sonja Khan,
School of Medicine
E: sonja.khan@universityofgalway.ie
What Experts Say
Prof Pavel Roshanov | External Examiner, MSc Applied Clinical Data Analytics.
Health and healthcare data are ever more plentiful, statistical software is free, and access to theoretical knowledge is available to everyone on the web, but the opportunity for apprenticeship with experts who combine clinical domain knowledge with statistics and research methodology is deeply valuable and hard to find. The new MSc in Applied Clinical Data Analytics combines traditional research methodology training with clinical data analytics through the R statistical programming language. It is taught directly by clinical researchers with backgrounds in epidemiology and data analytics who teach statistics and analytics in the research context where they will be used. This is a fantastic programme.in Connect with Prof Pavel
What Our Students Say
Aoife Boyle | Applied Clinical Data Analytics Student
Embarking on the Masters course in Applied Clinical Data Analytics has significantly enhanced my understanding of health research and critical analysis. The course has equipped me with the ability to scrutinise complex health data with precision and insight. My theoretical knowledge is now solidly underpinned by practical analytic skills, acquired through hands-on database analytics. I am excited to harness both facets of my skillset to advance my career as a clinical pharmacist in promoting evidence- based medicine in critical care and increase my involvement in the analytics of electronic datasets.
Dr. David Agular | Applied Clinical Data Analytics Student
During the MSc programme in Applied Clinical Data Analytics, I have come to understand the relationship between data analysis and various facets of research. From designing and implementing research methodologies to ensure data integrity and quality, to selecting and reporting analysis methods, this programme has equipped me with the necessary tools to produce reliable and comprehensible research outcomes. The practical approach of this programme, combined with the support and mentorship from faculty members, allowed me to cultivate a deeper proficiency in the different domains of data analysis, motivating me to pursue my academic and professional aspirations.
Dr. Reginald Cadlecott | Anaesthetist and Intensivist Registrar
As an Anaesthetist and Intensivist Registrar, my engagement with the MSc Clinical Data Analytics program at Galway University has been a profound journey of discovery and empowerment. The decision to enroll was motivated by a keen interest in enhancing my research methodologies and statistical analysis capabilities, which are pivotal in the dynamic and complex field of medical science. This programme exceeded my expectations, offering not just a solid theoretical foundation in clinical research and data analytics but also the practical acumen necessary for immediate application in the intensive care arena. The curriculum is meticulously crafted, integrating clinical practice with analytical science, and it equipped me with the skills to navigate and interpret vast intensivist databases effectively. This newfound proficiency in data analysis has significantly augmented my research activities and informed my clinical decisions. The diversity and expertise of the faculty, encompassing accomplished academicians, seasoned clinicians, and skilled data scientists, provided a rich learning environment. Their insights and guidance encouraged a culture of innovation and critical thinkin
Dr. Clodagh McDermott | Applied Clinical Data Analytics Student
The Master's in Applied Clinical Data Analytics provided me with a solid base to undertake my PhD in stroke medicine and machine learning. The masters offered me a solid foundation in clinical research through a focused and practical approach to applying data analytics and machine learning methodologies to real-world research questions. The blended approach to teaching research methodologies, statistics, and R programming significantly enhanced my learning experience. I not only gained competency in the R programming language, but I also developed a deeper understanding of its applications in data analysis, data visualisation, and machine learning; all skill-sets crucial for the modern medical researcher. The course content was thoughtfully developed, striking a balance between challenging and engaging content. My learning was supported by experienced, dedicated, and approachable lecturers who fostered a friendly learning environment. The Master's in Applied Clinical Data Analytics surpassed my expectations and has equipped me with invaluable skills and knowledge. For those aspiring to excel in healthcare research, this programme is an excellent choice.