HLTHINFO 730 : Healthcare Decision Support Systems

Medical and Health Sciences

2021 Semester Two (15 POINTS)

Course Prescription

Familiarises students with the main developments of decision support systems in healthcare. The theoretical concepts and the technology including data mining, clinical decision support systems, diagnostic systems and decision support in managed care are outlined. Ethical issues are also addressed.

Course Overview

The course provides students with a theoretical and practical background in healthcare decision support. The sequence of course topics is as follows:
  • Intro to role and motivation for automated decision support systems in healthcare
  • Encoding clinical information – formally representing facts about healthcare
  • Ontology, data warehousing, data linkage and data mining – how do they all relate?
Knowledge engineering
  • Decision trees (as a representation, and learning them automatically from data)
  • Production rule systems (IF-THEN systems, our main practical focus) and Case Based Reasoning (learning from past similar cases )
  • Probability and Fuzzy Logic
  • Evidence Based Medicine and Clinical Practice Guideline representations
  • Historical successes – and what makes for a success?
  • Enabling architectures – how to make it work and integrate with healthcare systems
  • Monitoring systems and mobile computing – some key rising areas
  • Evaluation – how to tell if a CDSS will be effective

Course Requirements

Restriction: POPLHLTH 730

Course Contacts

Coordinator and Lecturer: Dr. Seyedjamal (Jamal) Zolhavarieh. Email: j.zolhavarieh@auckland.ac.nz
For administrative aspects of the course such as your enrollment please contact Kashmira on k.irani@auckland.ac.nz

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement
Capability 5: Independence and Integrity
Capability 6: Social and Environmental Responsibilities
Graduate Profile: Master of Health Sciences

Learning Outcomes

By the end of this course, students will be able to:
  1. Apply a structured process of knowledge engineering to derive logical specifications for decision support from clinical practice guidelines written for humans (Capability 1.1, 1.2 and 3.1)
  2. Design (no programming required) a prototype rule-based decision support system (Capability 3.1, 3.2 and 5.2)
  3. Critically evaluate a decision support system in terms of provenance, agreement with practice guidelines, usability, fit to clinical workflow and maintainability (Capability 2.1, 5.1 and 6.1)
  4. Conduct independent research on technology concepts related to decision support systems (Capability 1.1, 2.2 and 5.2)
  5. Participate in informed discussion of decision support system concepts (using online means) (Capability 4.1, 4.2 and 5.2)
  6. Appreciate the role of decision support systems in healthcare, including tele-monitoring (Capability 4.1, 4.2 and 6.2)
  7. Discuss international standards development work in clinical guideline/knowledge representation and decision support system design (Capability 4.1, 5.1 and 6.1)
  8. Contribute to the design and successful implementation of healthcare decision support systems (Capability 3.1, 4.2 and 6.2)


Assessment Type Percentage Classification
Domain Modelling short video presentation 25% Individual Coursework
DSS Prototype 40% Individual Coursework
Evaluation Report 35% Individual Coursework
Assessment Type Learning Outcome Addressed
1 2 3 4 5 6 7 8
Domain Modelling short video presentation
DSS Prototype
Evaluation Report

Workload Expectations

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

For this course, you can expect 24 hours of lectures, a 12 hour tutorial, 24 hours of reading and thinking about the content and 90 hours of work on assignments and/or test preparation.

Delivery Mode


Attendance is not required at scheduled online activities to complete components of the course. Weekly course materials can be read at your time.
The course will include 2 to 3 live online events including group discussions/tutorials/lectures and these will be recorded.
Attendance on campus is not required for the assessments.
Where possible, study material will be released progressively throughout the course.
This course runs to the University semester timetable and all the associated completion dates and deadlines will apply.

Learning Resources

The course book provides references to illustrative readings organised according to the learning module sequence. Students should study the key readings, which together with the other learning activities, will reinforce understanding and increase analytical skills.
There is no set text for this course, but the following books can be accessed through the University library system:
Van de Velde R, Degoulet P. Clinical Information Systems: A Component-based Approach, Springer-Verlag, N.Y. 2003
Australian National Electronic Decision Taskforce, Electronic Decision Support for Australia’s Health Sector, Commonwealth Department of Health and Human Service, ACT, Australia. 2002
Shortliffe EH, et al (ed.), Medical Informatics: Computer Applications in Health Care and Biomedicine, 2nd edition, Springer, 2000
Slee VN, Slee DA, Schmidt HJ. The Endangered Medical Record: Ensuring its Integrity in the Age of Informatics. St. Paul, Minn: Triaga Press, 2000
Smith J, "An Overview of Health Information Management Systems", in Smith J, Health Management Information Systems, Open University, 2000
van Bemmel J.H., Musen, M.A. (editors) Handbook of Medical Informatics. AW Houten, Netherlands: Bohn Stafleu Van Loghum ; Heidelberg, Germany : Springer Verlag, 1997
Students should also consult journals such as the International Journal of Medical Informatics and Journal of the American Medical Informatics Association.

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.

Based on the feedback from students and the information received from the course, there are some rooms to be improved such as narrowing down some of concepts in lecture notes, setting more face to face or online sessions, deleting audio from ppt in course-builder and providing more precise video, refining assignment tutorials and providing more clear marking guideline, specifying course expectations on assignment tutorials, redesigning students contributions in Piazza. 
One of the great thing we have received as feedback from students were about sample assignment that we provided for students to give them clear idea how to prepare assignment. They were satisfied and it solved some of the confusion among students.

Other Information

The course is divided into online modules, each with a series of supporting resources, including lectures, readings from the international research literature and other activities (e.g., software tutorials and focus questions for online discussion). All materials are accessed via the Web and online discussions/peer feedback will be heavily used. Online participation and constructive criticism to other students are taken into consideration during marking. Course readings are available via the University Library's website. This is an online course with optional face to face sessions; one at the beginning of the semester and another one at the end of the semester. These will be recorded and put up on CANVAS for those who cannot attend the sessions.

Digital 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.

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 against online source material using computerised detection mechanisms.

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 your assessment is fair, and not compromised. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator, and if disruption occurs you should refer to the University Website for information about how to proceed.

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 you may be asked to submit your 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. The final decision on the completion mode for a test or examination, and remote invigilation arrangements where applicable, will be advised to students at least 10 days prior to the scheduled date of the assessment, or in the case of an examination when the examination timetable is published.