Healthtimeline app - helping patients and clinicians through data visualisation Co- Supervisor Name: Dr Miikka Ermes Email: miikka.ermes@flinders.edu.au The aim of this project is to assess feasibility, acceptability, usefulness and guide further development of the Healthtimeline app. Healthtimeline is a web based health records application aimed at patients, clinicians and researchers. It is developed in collaboration with National e- Health Transition Authority. The application facilitates access to health data stored in myhealthrecords (formerly known as PCEHR), Australia s national electronic health records infrastructure. Furthermore it utilizes innovative visual analytics to assist health professionals and patients easily infer clinical insights from historical events based data. It is designed to provide context during clinical interactions with patients and access to real time to Medicare health records in clinical research studies.
Designing tools for decision making and personalised feedback in health Co- Supervisor Name: Dr Miikka Ermes Email: miikka.ermes@flinders.edu.au The aim of this project is develop and evaluate tools for decision making and personalised feedback in health using two large datasets from diabetes and the Men Androgen Inflammation Lifestyle Environment and Stress (MAILES) Study
Health app use in young adults Co- Supervisor Name: Dr Peter Musiat Email: peter.musiat@flinders.edu.au The aim of this project is to understand the interplay between readily available health apps, personal characteristics and health behaviours. This study will make use of the Reachout cohort study data set.
Improving health care through data Co- Supervisor Name: Dr Miikka Ermes Email: miikka.ermes@flinders.edu.au This project aims to improve health care by combining various data sources. Specific aims are to: 1. Collect high resolution walking, sleep and diet data using wearables from hospital patients and readily available apps and integrate them with retrospectively available hospital data and other research data sets (including genotype information). 2. Analyze data to derive contexts, insights and actionable associations that can help develop better prevention care strategies or optimize care.
Digital footprints in depression Co- Supervisor Name: Dr Peter Musiat Email: peter.musiat@flinders.edu.au This project aims to collect high resolution walking, sleep and diet data using wearables from depressed and non- depressed patients in a naturalistic setting with an intention of linking them with genotyping QIMR patients.
Undertanding digital footprints - acceptability and access Co- Supervisor Name: Dr Peter Musiat Email: peter.musiat@flinders.edu.au Digital footprints describe the data we leave behind every day when interacting with any form of technology. This project is designed for two students with either backgrounds in health or computer sciences to explorethe acceptabiliy and access of readily available digital footprints (eg., online shopping, banking, wearables, social media, email interactions, etc) and feasibility of obtaining this data in a small sample. 1. What information are people willing to share and what are facilitators and barriers of this? 2. How can these records be conveniently obtained?