DIGIHLTH 706 : Health Data Analytics

Medical and Health Sciences

2024 Semester Two (1245) (15 POINTS)

Course Prescription

Analyses, interprets, and presents quantitative data to assist decision making in the health sector. Fundamental elements of statistics, data management, visualisation, epidemiology and computing are covered.

Course Overview

The objective of this course is to develop skills and confidence in extracting meaning from data.  
Health practice and research both inform and are informed by the evidence base, much of which is represented by quantitative summaries, figures, models and statistical tests.  It is important to be able to critically evaluate existing evidence for it's relevance to a current situation yet the skills or knowledge needed to do that aren't always included in our professional training.

This course will place emphasis on interpreting the results of statistical summaries and tests in the context of health and the health system. In addition to summary statistics, data visualisation, correlation and model coefficients, we will investigate just what statistical significance does and doesn't mean.  We will then move on to the pros and cons of categorising continuous measurements, the development and use of reference values, and the key things to think about in a meta-analysis.  A plethora of tools, devices, algorithms, and scores exist in health, with more added every day, so we will introduce how to assess their performance, enabling critical evaluation of their suitability to a given situation.  Throughout, we will use iNZight software to support your learning. You do not need to have used statistical software before.

Course Requirements

No pre-requisites or restrictions

Course Contacts

Assoc Prof Katrina Poppe | Course Director

Katrina is a health data scientist and clinical cardiac physiologist with extensive experience in health and disease from the perspectives of clinical practice, clinical and epidemiological research and biostatistics. Based in the Faculty of Medical and Health Sciences at the University of Auckland, she leads research and teams, is the director of data and analytical practice of the  VAREANZ (Vascular Risk Equity for Aotearoa NZ) national programme of cardiovascular research, chairs the data science advisory groups of several longitudinal research projects, and is a co-director of the University's new Health Data Platform. She contributes to the evolving field of health data science through clinical, epidemiological and methodological research and teaching, with a focus on the meaningful use of ‘big health data’ to augment clinical research and practice. She has developed internationally relevant reference ranges for cardiac markers, national cardiovascular risk scores, and has specific research interests in the areas of heart failure and atrial fibrillation.

Capabilities Developed in this Course

Capability 3: Knowledge and Practice
Capability 4: Critical Thinking
Capability 5: Solution Seeking

Learning Outcomes

By the end of this course, students will be able to:
  1. Extract findings from data (Capability 3 and 5)
  2. Critically review and assess the knowledge base (Capability 3 and 4)
  3. Assess and discuss the performance of health tools (Capability 4 and 5)
  4. Develop fundamental skills in data manipulation (Capability 3)


Assessment Type Percentage Classification
Assignment 1 - know your data 15% Individual Coursework
Assignment 2 - use existing data 25% Individual Coursework
Assignment 3 - assess performance 30% Individual Coursework
Assignment 4 - bring it all together 30% Individual Coursework
Assessment Type Learning Outcome Addressed
1 2 3 4
Assignment 1 - know your data
Assignment 2 - use existing data
Assignment 3 - assess performance
Assignment 4 - bring it all together

Workload Expectations

This course is a standard 15 point course and students are expected to spend at least 10 hours per week involved in each 15 point course that they are enrolled in.

Delivery Mode


The course may include live online events including group discussions or tutorials and these will be recorded.
Where possible, study material will be available at course commencement.
This course runs to the University semester/quarter timetable and all the associated completion dates and deadlines will apply.

Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Freely available software iNZight will be used for data visualisation and analysis.

Student Feedback

At the end of every semester students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback and respond with summaries and actions.

Your feedback helps teachers to improve the course and its delivery for future students.

Class Representatives in each class can take feedback to the department and faculty staff-student consultative committees.

The course was first run in Semester 2 2023. More live group discussions will be scheduled next year, and the assignments will be reviewed.  The course has attracted students from a very wide range of backgrounds and experience with data and/or health, and many had EAL, so all questions will be reviewed for ambiguity.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed for potential plagiarism or other forms of academic misconduct, using computerised detection mechanisms.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption, we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.

The delivery mode may change depending on COVID restrictions. Any changes will be communicated through Canvas.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html.


Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course students may be asked to submit coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.