Big Data and the Learning Health System
Platforms for Impact
Risk prediction project Gravitar is using machine learning with routine pregnancy care data to predict women who have a high risk of developing gestational diabetes or a hypertensive disorder in pregnancy
Supporting researchers to get the most from big data in health to improve health, health systems and policy. Big data, machine learning and risk prediction modelling are areas we have a current focus.
We underpin this research platform with the best-practices for LHS development and implementation, as well as also further developing the LHS field.
A Learning health systems (LHS) can be broadly defined as a cyclical and continually-updating process that collects and analyses health-systems data to inform practice and ultimately, improve healthcare. When correctly implemented, an LHS can be an extremely powerful tool for effectively gathering insights from big-data (such as electronic health records).
Health related data holds major promise and potential to improve healthcare, build systems that are resilient to crises such as the COVID-19 pandemic, and inform current and future health system transformation. The Learning Health Systems (LHS) can be an extremely effective way to harness this data for healthcare improvement.
This platform supports researchers to get the most from big data in to ultimately improve Australian healthcare systems and deliver optimal health to Australians by: 1) identify and address the barriers to the full utilisation of healthcare data, and; 2) accelerate and implement an innovative National Learning Health System Data Management Platform underpinning a sustainable Learning Health System.
We draw on strategic partnerships and established governance and investment across the Monash Partners (MP) Learning Health System, the Monash University Helix data system, the Victorian Government Collaborative Healthcare Recovery Initiative, the Australian Health Research Alliance data driven healthcare improvement initiative, international partnership. We engage across acute (public and private), primary and aged care, academia, government and industry.
Implementation & Impact
By definition, the scope of the project is broad, as we aim to implement an LHS to continually improve healthcare within health settings and policy. Our findings will impact several hundreds of thousands of service users (who come from diverse socioeconomic backgrounds), and potential for impact Australia-wide and globally.
- Towards a National Data Management Platform and Learning Health System
- Formalising the Science of Learning Health Systems:
- Case Studies in Meta-Research & Maternal Health
- Can a perioperative learning health system provide a model for achieving the Quadruple Aim?
- Risk prediciton and perception – cardiometabolic diseases during pregnancy
- Using AI to Predict Risk of Extended Length of Stay in Admissions to Hospitals in Australia
- Using AI to Predict Clinical Risk in Mental Health/Alcohol and Drug Services
- How to optimise EHR use within and between a tertiary hospital and other providers
- Healthy lifestyle in Preconception, Pregnancy and Postpartum – HiPPPP- Personalised Medicine meets Public Health in the first 2000 days
- Optimising the delivery of antenatal interventions in public healthcare: Improving equity, access and engagement for better maternal and neonatal health outcomes
- The use and utility of My Health Record in the emergency department
- Determinants and patterns of hospital admissions among patients with chronic disease
- Innovative statistical methods to improve women’s health
- Gestational weight gain and risk of adverse maternal and neonatal outcomes
To deliver health impact, we use the following MCHRI platforms
Kushan De Silva, Darren Rajit, Cameron Graydon, Swapna Gokhale, Demelash Woldeyohannes Handiso, Sofonyas Tiruneh, Yitayeh Belsti
Student Research Projects
This team offers a variety of Honours, Masters and PhD projects for students. There are also a number of short-term research opportunities available. You are encouraged to get in touch regarding potential projects that align with the research areas.
We gratefully acknowledge the funding given to our group by the following groups:
- Heart Foundation
- Victorian Govt
- Monash Partners and member organisations