My research investigates parent and clinician preferences for a neurodevelopmental model of care to improve outcomes for children with congenital heart disease (CHD) in order to improve how models of care are designed and delivered.
Implementation activities are not often costed and there aren’t many approaches to cost implementation. This can lead to inefficient use of scarce healthcare resources. My PhD aims to address this need by developing an implementation costing tool to help with estimating the true cost of implementing digital health solutions in hospitals.
My research looks at ways in which digital health systems can assist in the reduction of non-attendance at scheduled outpatient healthcare appointments. The project aims to provide insights into the impact of non-attendance, and consumer preferences and cost-effectiveness for interventions that may be used to reduce non-attendance.
My research investigates how we can take advantage of implementation science approaches to adopt computerised Clinical Decision Support Systems (CDSS) within hospital settings. The aim of my project is to increase awareness around what changes may be needed to improve the process.
My PhD research is focused on understanding what makes clinical decision support models useful for addressing clinical deterioration. My project will consist of a series of related studies.
My project is all about developing and evaluating prediction models for hospital falls. To do this, we have partnered with Metro South Health and will be using the data within integrated electronic medical records (ieMR) for patients admitted across any of their hospitals.
