Case based learning software for digital health skills training

To ensure our graduates are competent in the use of digital health technologies, the Department of Nursing developed a strategy to embed digital health in the Master of Nursing Science entry-to-practice curriculum.

Image of student using workstation on wheels with a patient To optimise student engagement in the use of digital health technologies as part of their learning, the department first purchased twenty mobile computers (workstations on wheels) and resourced patient management software in 2020 for use in the clinical simulated learning environment during clinical skills sessions.

In March 2022 the Department of Nursing switched to using Case Based Learning Software, an Australian-based Electronic Medical Records (EMR) training platform, into the Master of Nursing Science entry-to-practice curriculum. This tool was developed by the Commonwealth Scientific Industrial and Research Organisation (CSIRO) in consultation with the University of Queensland.

The Case Based Learning (CBL) Software is a teaching tool designed to support case-based learning via custom-built “cases” in an EMR. This approach is intended to support the development of digital literacy via engagement with an EMR and to enhance the pedagogy of case-based learning by providing more opportunities for clinical decision-making.

Image of Workstation on wheelsAs part of their course, students are presented with a series of standardised clinical cases in an EMR, where they are expected to assess clinical information and respond to changes occurring during the cases’ simulated hospital admission. Throughout the cases, students are expected to develop their digital and critical thinking skills by using the software to make clinical judgements, document or communicate findings and/ or explain their decision-making.

The CBL software has now been used by 173 first-year and 154 second-year Master of Nursing Science students. Evaluation of the student/educator experience, acceptability and usability of this software is underway. Results will be available in early 2023.