Ocular Imaging and Telemedicine
The Australian e-Health Research Centre's Western Australia node conducts research projects investigating the use of ocular imaging and telemedicine in disease early detection and monitoring. The current focus of the project is the development of non-invasive ocular imaging techniques in Alhzeimer's Disease and other neuro-degenerative diseases.
More...Health Data Integration (HDI) (Core Project 1)
This project is developing software tools for linking, integrating and analysing data for cancer patients, in conjunction with Queensland Health's cancer program. The major challenge is to achieve interoperability for medical records held in disparate databases while preserving the privacy of patients. The project is delivering large-scale coordination of databases to improve quality and safety in health care.
Queensland Health, through the Queensland Cancer Control and Analysis Team (QCCAT) has been working with the Australian e-Health Research Centre in a program to link cancer data sets across Queensland. This continues as an on-going project at QCCAT with software and data analysis support from the Australian e-Health Research Centre. The research program has been extended to linking of other clinical and operational data sets. More...
Health Information Environment/Systems (HIE/S)
Australian e-Health Research Centre researchers and engineers are developing novel applications for the processing and use of health and medical data. Health and medical data is stored using any number of technologies and formats with differing requirements of privacy and security.
The technical and application domains which are of interest to our researchers and engineers include:
- database and data integration technology
- clustering and analysis of patient data
- electronic health records
- ontology engineering
- query and retrieval of complex data
- natural language processing
Cancer Stage Interpretation System (CSIS) (Core Project 3)
This project builds upon a core CSIRO research capability in multimedia content analysis within the health domain, focusing on a particular application: support systems for cancer management, both for individual patients and population-level analyses. More...
Care Assessment Platform (CAP) (Core Project 6)
The Australian e-Health Research Centre will conduct clinical trials in conjunction with the Redcliffe-Caboolture Health Service District across the local community primary healthcare setting to develop a prototype of a Care Assessment Platform to enable clinical assessment of functional capacity and the underlying physiological condition among a cohort of chest pain and chronic obstructive pulmonary diseases(COPD) patients in the community. More...
Biomedical Imaging
CSIRO researchers are developing new tools to analyse and extract valuable information from medical images, such as magnetic resonance imaging (anatomical, functional, spectroscopy), computed tomography, positron emission tomography, ultrasound imaging, molecular imaging, and histology imaging. More...
AMIDA (Augmented Multi-party Interaction with Distant Access) (Partner Project 3)
AMIDA commenced in October 2006 as an Integrated Project in the European Union's 6th Framework Programme. As a partner in AMIDA, the Australian e-Health Research Centre is collaborating with a consortium of 12 international research partners coordinated by the University of Edinburgh (UK) and the IDIAP Research Institute (Switzerland).
The AMIDA project is researching technologies that support human communication in co-located and distributed team meetings, and involves several disciplines including:
- Qualitative human analysis and human factors
- Audio-video processing, including unconstrained speech recognition and natural scene analysis
- Multimodal structure and content analysis, including the modelling of individuals and groups, through the joint processing of multiple (multimodal) information channels (audio, visual, slides, handwriting, and white board activity)
- Human Computer Interface, application prototyping, evaluation, and system integration
In collaboration with Griffith University and Qld Health, we are recording multi disciplinary team meetings. These recordings are then annotated for inter-personal interactions. These annotations are then analysed for traits and patterns which indicate successful team communication, leading to a high performing team which achieves its aims.
The AEHRC has built a prototype software tool which synchronises multiple video and audio recordings of the same meeting. The tool automatically performs some analysis, including speaker segmentation and some automated annotation. Our researchers are then able to use the tool to analyse the annotations for patterns of interactions in the meetings.
Queensland Facility for Advanced Bioinformatics (QFAB) (Partner Project 4)
QFAB commenced operations in December 2006 upon the signing of agreements with the Queensland Government through the Department of State Development and Trade. Professor Mark Ragan from The Institute for Molecular Bioscience (IMB) at The University of Queensland and Dr Anthony Maeder from the Australian e-Health Research were awarded a research grant of $1.9 million to establish QFAB through Round 1 of the Smart State Innovation Funds. The funding is being used to develop a facility that will support innovation within the Queensland biotechnology, health and the ICT sectors offering integrated data and high performance computing in a secure environment with affordable bandwidth and access to expert personnel.
QFAB is an unincorporated joint venture between The University of Queensland, Griffith University, Queensland University if Technology, Australian e-Health Research Centre, Queensland Department of Primary Industries and Fisheries, Queensland Parallel Supercomputing Foundation and the Australian Partnership in Advanced Computing. QFAB is located at the IMB.
Australian Cancer Grid – Merging of colorectal cancer surveillance databases from tertiary institutions across states (Partner Project 5)
This project aimed to integrate disparate databases of bowel cancer surveillance information from two states and tertiary institutions, and provide that integrated dataset for analysis of program efficacy and outcomes. At the completion of the first phase of the project, a standardised dataset has been established. This task was complicated by the differences in definition and representation of clinical concepts across sites, as well as the need to turn data sets used for running a surveillance program into data suitable for research and analysis. In many instances the extensive data cleaning required a return to paper based patient records to confirm details incorrectly entered into data sets, or that were originally interpreted against different definitions of clinical concepts. Analysis of this data is underway, and will be published accordingly.
In the next phase, other data sources will be incorporated to expand the information available for each patient and episode of care, eg individual mutation status and surgical results may be included.
This project is an ongoing initiative of Science Technology and Innovation Infrastructure Grants Program Victoria and CSIRO Preventative Health Flagship.
Robina ED Impact Study (REDI) and Ambulance Ramping Research (PAH)
AEHRC has established a strong collaboration with the Southern Area Health Service Emergency Department Clinical Network, contributing to the automated linking of patient information to support their research in emergency medicine. The centre has developed an innovative linking algorithm to ensure accurate matching of data for a specific episode of care for a patient. Using AEHRC's HDI software and this new algorithm, the time and effort required to integrate ambulance, emergency and admissions data has been greatly reduced - allowing greater time for in depth analysis.
Patient Admission Prediction Project
Accurate forecasting will assist many areas of health management, from basic bed management and staff resourcing to scheduling elective surgery. However by more accurately forecasting load there will also be a reduction in stress for staff and an improvement in patient outcomes. Emergency departments already know there's a pattern to presentations and admissions, but existing models are very simplistic.
Collaborating with clinicians from Gold Coast and Toowoomba Hospitals and Griffith University and Queensland University of Technology, The Australian e-Health Research Centre has developed a software package to assist hospital emergency medical staff predict demand on their services. The Patient Admission Prediction Tool (PAPT) will allow on-the-ground staff to see what the patient load will be like in the next hour, the rest of the day, into next week, or even on holidays with varying dates, such as Easter. PAPT uses historical data to provide an accurate prediction of the expected load on any day.
The PAPT tool has been validated and shown to vastly improve successful prediction of patient presentation and admission in two hospitals with very different populations. Importantly the tool was designed after user meetings with over 15 bed managers and hospital administrators performed by our collaborators at Griffith University. The AEHRC is aiming to evaluate the impact of the tool at major hospitals over the next 12 months.
Project collaborators include Queensland Health, Griffith University and Queensland University of Technology.
PhD Sponsorship (Affiliate Project 1)
This Australian e-Health Research Centre sponsored PhD project will investigate the use of trusted agents in a distributed intelligence approach to the problem of interrogating multiple independent databases without compromising data privacy. This approach will allow local processing of data such as data mining, inexact matching or statistical analysis, in order to process global queries more efficiently and securely.
PhD Sponsorship (Affiliate Project 2)
This Australian e-Health Research Centre sponsored PhD project addresses issues of resource management and scheduling in health systems. The complexity and changeability of interacting factors affecting the assignment of resources demands a very flexible and dynamic solution, in order to achieve a high level of utilization and cater for many different competing priorities. The project will provide a compound strategy for optimization of resource allocation under time varying circumstances.
PHD Sponsorship (Affiliate Project 5)
This Australian e-Health Research Centre sponsored PhD project will investigate if immobilization of older patients is a major contributing factor to their long length of stay in hospital. This will be achieved through clinical trials of ambulatory monitoring conducted on older patients to record their movement during their stay in a hospital setting. From this, signal processing and data analysis will be performed to quantify mobilisation and functional status of patients to characterise their level of immobilisation. Moreover, the analysis will aim to demonstrate if areas of improvement in mobility and functional status can reduce older patients' stay in hospital.
PhD Sponsorship: Clinical networks: can more effective clinical leadership in decision making improve the effectiveness of clinical networks? (Affiliate Project 7)
Griffith University, Australian e-Health Research Centre and Queensland Health Collaborative Research Project
Clinical networks have been established to enable clinicians to more fully participate in the management of health services in Queensland. They represent a new organizational entity which promises to enhance coordination between services; facilitate better access to services and improve outcomes. Current evidence suggests that effective network based organisations require leaders who have innovative problem solving skills, the ability to manage group decision making and a readiness to engage in reciprocal behaviours.
This research project will identify which leadership behaviors and group interactions are associated with the effectiveness of clinical networks. The project will utilise recent developments in IT tools which enable the annotation and analysis of speakers and meetings and provide a promising avenue for the automated collection, coding and analysis for the empirical study of clinical group decision making.
