DIGIHLTH 704 : Healthcare Decision Support Systems
Medical and Health Sciences
2024 Semester Two (1245) (15 POINTS)
Course Prescription
Course Overview
- 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?
- 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 success?
- Enabling architectures – how to design 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
Capabilities Developed in this Course
| Capability 1: | People and Place |
| Capability 2: | Sustainability |
| Capability 3: | Knowledge and Practice |
| Capability 4: | Critical Thinking |
| Capability 5: | Solution Seeking |
| Capability 6: | Communication |
| Capability 7: | Collaboration |
| Capability 8: | Ethics and Professionalism |
Learning Outcomes
- Understand and apply knowledge engineering principles to conceptualize and design decision support systems. (Capability 3 and 5)
- Critically evaluate various aspects of decision support systems and engage in independent research to enhance understanding of related technologies. (Capability 3 and 4)
- Engage in informed discussions on relevant topics and comprehend international standards and developments in the field. (Capability 6 and 7)
- Appreciate the role of decision support systems in healthcare, including tele-monitoring (Capability 1 and 3)
- Recognize the broader role and impact of decision support systems within the healthcare ecosystem. (Capability 1 and 2)
- Contribute to and understand the ethical implications of designing and implementing decision support systems in healthcare. (Capability 5 and 8)
Assessments
| Assessment Type | Percentage | Classification |
|---|---|---|
| Domain Modelling short video presentation | 25% | Individual Coursework |
| DSS Prototype | 40% | Individual Coursework |
| Evaluation Report | 35% | Individual Coursework |
| 3 types | 100% |
| Assessment Type | Learning Outcome Addressed | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | |||||
| 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, 12 hours of tutorial, 24 hours of reading and thinking about the content and 90 hours of work on assignments and/or test preparation.
Delivery Mode
Online
This course is delivered in online, or distance mode. In other words, you will be able to complete the course without physically attending lectures, seminars or tutorials on campus. This is how it works.
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.
Although there are no days blocked off for lectures, there will be plenty of opportunity to interact with other students in the class, your lecturer and other university staff associated with the course. We recommend the online discussions (via Piazza) as your primary mode of communication, although sometimes direct email, Skype or telephone may be appropriate.
The approach assumes that lecturers and students work together in a collaborative fashion using the readings and other materials in the 12 weeks, as well as assignment work, to create a framework for discussion and illustration of key principles. While some people may feel more comfortable offering comment than others, you can share your views and ideas, voice questions or doubts and introduce relevant articles or events. Digital Health is an evolving and applied discipline - insights from your own experiences make a valued contribution to the course.
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.
- Shortliffe, H. Edward, and J. James Cimino. Biomedical informatics: computer applications in health care and biomedicine. Springer-Verlag London. 2021.
- Berner ES, La Lande TJ. Overview of clinical decision support systems. Clinical decision support systems: Theory and practice. 2016.
- Yang J, Kang U, Lee Y. Clinical decision support system in medical knowledge literature review. Information Technology and Management. 2016.
- 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
- 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
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.
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.
Disclaimer
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.