OPSMGT 700 : Healthcare Analytics and Operations

Business and Economics

2025 Semester One (1253) (15 POINTS)

Course Prescription

Addresses techniques for data-driven decision-making in healthcare. Issues faced when managing healthcare operations will be discussed, with particular reference to the New Zealand context. Mathematical and computer-based techniques for managing operations under uncertainty will be introduced, with a focus on how they can be applied in practice in a healthcare setting.

Course Overview

Healthcare systems are inherently complex, with many uncertainties and operational challenges. This course introduces techniques for data-driven decision-making in operations. Whilst the particular focus of this course is healthcare, many of the techniques and concepts covered can also be applied in other fields. Students will be introduced to a selection of mathematical modelling and computer-based techniques to solve problems in healthcare operations. As the implementation of these techniques typically involves the use of data, relevant analytics tools will also be introduced. The course will address issues such as model and tool selection, justification of modelling assumptions, and the use of modelling results in decision-making. This course will draw on both the academic literature and case studies.

Course Requirements

Prerequisite: STATS 201, 208, 210, 225 or equivalent

Capabilities Developed in this Course

Capability 3: Knowledge and Practice
Capability 4: Critical Thinking
Capability 5: Solution Seeking
Capability 6: Communication
Graduate Profile: Master of Commerce

Learning Outcomes

By the end of this course, students will be able to:
  1. Understand and explain the principles of a range of mathematical models for managing operations in uncertain environments. (Capability 3)
  2. Identify and apply appropriate analytics and modelling techniques to solve a variety of problems related to healthcare operations (Capability 3, 4 and 5)
  3. Communicate the results, implications, biases, and limitations of analysis effectively, both as a team and individually, with a focus on healthcare applications. (Capability 6.1 and 6.2)
  4. Critically evaluate the effectiveness and limitations of different data-driven decision-making approaches in managing healthcare operations (Capability 3 and 4)

Assessments

Assessment Type Percentage Classification
Assignments 40% Individual Coursework
Test 30% Individual Test
Project 30% Group & Individual Coursework
Assessment Type Learning Outcome Addressed
1 2 3 4
Assignments
Test
Project

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 2 hours of lectures, a 2 hour lab, 3 hours of reading and thinking about the content and 3 hours of work on assignments and/or test preparation.

Delivery Mode

Campus Experience

Attendance is required at scheduled activities, including quizzes and labs, to receive credit for components of the course. 
Lectures will be available as recordings. Other learning activities, including labs, will not be available as recordings.
Attendance on campus is required for the test.
The activities for the course are scheduled as a standard weekly timetable.

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.

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.

Feedback will be used to improve the course for the current and future semesters.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework, tests and examinations 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. A student's assessed work may be reviewed against electronic source material using computerised detection mechanisms. Upon reasonable request, students may be required to provide an electronic version of their work for computerised review.

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 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.

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 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.

Published on 11/11/2024 09:53 a.m.