Our priorities are to:

• Create virtual or actual health data research hubs within the Academic Heath Science Centres to stimulate partnerships across academic, clinician and industry stakeholders
• Integrate large scale data sets to undertake research and quality improvement across the primary care, acute and sub-acute continuum, including electronic medical record related activity
• Build workforce capacity in data use for health care improvement
• Enhance access to and presentation of registry data, and facilitate integration and linkages between registry data and other data sources
• Integrate with the Monash University data platforms in order to strengthen and build our data infrastructure and systems.
  • Helix
  • Secure eResearch Platform (SeRP)

The Platform is led by

The Data Driven Healthcare and Informatics Committee brings together researchers, data specialists, clinicians and consumers from across Monash Partners.

They include:

• Professor Carol Hodgson (Lead)
• Associate Professor Susannah Ahern
• Dr Robab Abdolkhani
• Dr Nadine Andrew
• Professor Peter Cameron
• Ms Deborah Dell
• Dr Joanne Enticott
• Dr Angus Henderson
• Ms Jennifer Irving (Consumer Partner)
• Mr Thomas Lew
• Ms Jane Loke
• Mr Lachlan McBean
• Ms Erica Potts
• Mr Adam McLeod
• Ms Tanya Ravipati
• Professor David Taylor
• Mr Daniel Topham
• Mr Arne Protz

Below you will find useful resources focused on Data-Driven Healthcare and Informatics. For further information contact Ms Alison Johnson via email: c-informp@monash.edu.

Data linkage and integration

Data linkage is a method of bringing information from different sources together about the same person or entity to create a new, richer dataset. (Menzies Institute for Medical Research)

Following are a number of institutions that specialise in providing data linkage services. Some do this as their only activity, whilst others combine this with educational and other support services. This is not an exhaustive list and these organisations are presented in alphabetical order.

The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) is an open community data standard, designed to standardize the structure and content of observational data and to enable efficient analyses that can produce reliable evidence. A central component of the OMOP CDM is the OHDSI standardized vocabularies. The OHDSI vocabularies allow organization and standardization of medical terms to be used across the various clinical domains of the OMOP common data model and enable standardized analytics that leverage the knowledge base when constructing exposure and outcome phenotypes and other features within characterization, population-level effect estimation, and patient-level prediction studies.

AIHW – Australian Institute of Health and Welfare

is a leading health and welfare statistics agency in Australia. They improve the health and welfare of all Australians by making available information and statistics that can help shape and improve the health of our community through better services and programs.  

Information about current data linkage projects at the AIHW can be found HERE.

ARDC – Australian Research Data Commons

ARDC enables Australian researchers and the eResearch community access to data intensive infrastructure, platforms, skills and collections of high-quality data.

Two resources of particular relevance are:

• Good Data Practices
• ARDC Resources Hub

Four services of particular relevance are:

• ARDC Nectar Research Cloud

This service provides Australia’s research community with computing infrastructure and software.

• Research Data Australia

An online portal for finding research data and associated projects, researchers, and data services. You can find, access, and reuse data for research from over one hundred Australian research organisations, government agencies, and cultural institutions.

• Health Studies Australian National Data Asset (HeSANDA)

The HeSANDA program is building national infrastructure to allow researchers to access and share data from health studies, including clinical trials.

• Identifier services

Create and manage persistent identifiers for research data, research samples, files, documents or other digital objects.

Seven of the nine nodes working on this project are AHRA centres. Monash Partners and Monash University together form one of these.

PHRN – Population Health Research Network

A national collaboration that enables existing data from around Australia to be brought together and made available for important research. Databases include birth, marriage and death records as well as some health data records.

CVDL – The Centre for Victorian Data Linkage

Is the Victorian state node of the Population Health Research Network. Based in the Department of Health and Human Services, its main function is to create and maintain linkages within and between Victorian government, health and non-health administrative data collections, and extend the capability for building a nationwide data linkage infrastructure. Data that can be linked are represented in this diagram:

 

Monash Clinical Registries

Monitoring variation in healthcare is known to support best practice and improve quality of care. However, challenges exist in developing and accessing appropriate data sets on which to undertake clinical quality benchmarking. Clinical registries are increasingly recognised as credible, effective and feasible tools to measure variation and drive quality improvement at the national and jurisdictional health system levels.

Monash University Helix platform

Monash University’s medical researchers and their collaborators are at the forefront of Health, Epidemiological and Translational research nationally and internationally. The University, recognising health data management as part of a crucial infrastructure for its research community, has committed significant investments and established Helix to harness digital innovation for sensitive research data.

Monash Secure eResearch Platform (SeRP)

is a secure environment for sharing research data for collaboration and analysis, within the control and governance of the data custodian. Monash SeRP allows the Data custodian or the delegated project manager (Data Custodian) to have visibility and control over how their data is being used by other approved researchers.

Australian Centre for Value Based Healthcare

Established by the Australian Healthcare and Hospitals Association, the Australian Centre for Value-Based Health Care’s vision is for a healthy Australia, supported by the best possible health care system.

Learning Health System data (LHS)

Background

The Australian Health Research Alliance’s (AHRA) Data-Driven Healthcare Improvement met in 2018 and agreed upon eight priority areas. The first of these is to create Learning Health System data hubs (term used previously – incubator hubs).

The Monash Partners Data-Driven Healthcare Improvement committee have also endorsed this priority.

Learning Health Systems data hubs (LHS data hubs) use data from clinical encounters and other health-related events, analyse the data to generate new knowledge, and then provide this knowledge to continuously inform and improve health decision making and practice, and patient outcomes. Data hubs require integrated and relevant workforce capacities (informaticians, frontline clinicians, researchers and community members), infrastructure, and governance. Data hubs fit well within the broader Learning Health Systems (LHS) framework.

Other Australian Learning Health Systems

Macquarie University 

The Centre for Healthcare Resilience and Implementation Science, at Macquarie University, has many publications related to health service change, and specifically in the area of Learning Health Systems. Here are Clinical applications of health systems research articles by Professor Braithwaite (Director of the Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation)

Melbourne University

The Learning Health System Academy has been developed by the Centre for Digital Transformation of Health at The University of Melbourne to:

• Build our healthcare workforce capacity for data-driven and digital health-enabled clinical practice improvement
• Truly transform healthcare through data-informed and technology-enhanced models of care
• Enhance patient and end-user engagement in the digital transformation of health.

International Learning Health Systems

Center for Clinical & Translational Science & Training

is a collaboration of the University of Cincinnati and the Cincinnati Children’s and are leaders in the use of Learning Health Systems to support health service improvement.

National Academy of Medicine

is one of three academies that make up the National Academies of Sciences, Engineering, and Medicine (the National Academies) in the United States. Operating under the 1863 Congressional charter of the National Academy of Sciences, the National Academies are private, nonprofit institutions that work outside of government to provide objective advice on matters of science, technology, and health.

Articles of Interest for LHS

Braithwaite J, Vincent C, Garcia-Elorrio E, Imanaka Y, Nicklin W, Sodzi-Tettey S, et al. Transformational improvement in quality care and health systems: the next decade. BMC Medicine. 2020;18(1):340.

Budrionis A, Bellika JG. The Learning Healthcare System: Where are we now? A systematic review. J Biomed Inform. 2016;64:87-92.

Dammery, G., Ellis, L.A., Churruca, K. et al. The journey to a learning health system in primary care: a qualitative case study utilising an embedded research approach. BMC Prim. Care 24, 22 (2023). https://doi.org/10.1186/s12875-022-01955-w

Darran Foo, Janani Mahadeva, Francisco Lopez, Louise A Ellis, Kate Churruca, Genevieve Dammery, Simon Willcock, Jeffrey Braithwaite. British Journal of General Practice 2023; 73 (726): 8-9. DOI: 10.3399/bjgp23X731505

Ellis LA, Sarkies M, Churruca K, Dammery G, Meulenbroeks I, Smith CL, et al. The Science of Learning Health Systems: Scoping Review of Empirical Research. JMIR Med Inform. 2022;10(2):e34907.

Enticott JC, Melder A, Johnson A, Jones A, Shaw T, Keech W, et al. A Learning Health System Framework to Operationalize Health Data to Improve Quality Care: An Australian Perspective. Frontiers in Medicine. 2021;8.

Enticott J, Braaf S, Johnson A, Jones A, Teede HJ. Leaders’ perspectives on learning health systems: a qualitative study. BMC Health Services Research. 2020;20(1):1087.

Enticott J, Johnson A, Teede H. Learning health systems using data to drive healthcare improvement and impact: a systematic review. BMC Health Services Research. 2021;21(1):200.

Forrest CB, Margolis P, Seid M, Colletti RB. PEDSnet: how a prototype pediatric learning health system is being expanded into a national network. Health Aff (Millwood). 2014;33(7):1171-7.

Friedman CP, Rubin JC, Sullivan KJ. Toward an Information Infrastructure for Global Health Improvement. Yearb Med Inform. 2017;26(1):16-23.

Greene SM, Reid RJ, Larson EB. Implementing the learning health system: from concept to action. Ann Intern Med. 2012;157(3):207-10.

Institute of Medicine (US) Roundtable on Evidence-Based Medicine;, Olsen LA, Aisner D, McGinnis JM, editors. The Learning Healthcare System: Workshop Summary. Washington (DC); 2007.

Juhn Y, Liu H. Artificial intelligence approaches using natural language processing to advance EHR-based clinical research. Journal of Allergy and Clinical Immunology. 2020;145(2):463-9.

Lannon C, Schuler CL, Seid M, Provost LP, Fuller S, Purcell D, et al. A maturity grid assessment tool for learning networks. Learning Health Systems. 2021;5(2):e10232.

Melder A, Robinson T, McLoughlin I, Iedema R, Teede H. An overview of healthcare improvement: unpacking the complexity for clinicians and managers in a learning health system. Intern Med J. 2020;50(10):1174-84.

Menear M, Blanchette M-A, Demers-Payette O, Roy D. A framework for value-creating learning health systems. Health Research Policy and Systems. 2019;17(1):79.

Platt JE, Raj M, Wienroth M. An Analysis of the Learning Health System in Its First Decade in Practice: Scoping Review. J Med Internet Res. 2020;22(3):e17026.

Psek WA, Stametz RA, Bailey-Davis LD, Davis D, Darer J, Faucett WA, et al. Operationalizing the learning health care system in an integrated delivery system. EGEMS (Wash DC). 2015;3(1):1122.

Reddy S, Rogers W, Makinen V-P, Coiera E, Brown P, Wenzel M, et al. Evaluation framework to guide implementation of AI systems into healthcare settings. BMJ Health & Care Informatics. 2021;28(1):e100444.

Seid M, Hartley DM, Margolis PA. A science of collaborative learning health systems. Learn Health Syst. 2021;5(3):e10278.

Young IJB, Luz S, Lone N. A systematic review of natural language processing for classification tasks in the field of incident reporting and adverse event analysis. International Journal of Medical Informatics. 2019;132:103971.

Zurynski Y, Smith Kl, Vedovi A, Ellis L, Knaggs G, Meulenbroeks I, et al. MAPPING THE LEARNING HEALTH SYSTEM: A SCOPING REVIEW OF CURRENT EVIDENCE. 2020.

Monash Partners Publications

Eastwood K, Johnson A, Jones A, Cameron P, Teede H. Data harmonization of Australian and New Zealand Ambulance Service Datasets. EMS2020, Glasgow, Scotland, 4-6 May, 2022

Joanne C. Enticott,  Angela Melder, Alison Johnson,  Angela Jones,  Tim Shaw, Wendy Keech, Jim Buttery and  Helena Teede. A Learning health system framework to operationalise health data to improve quality care: an Australian perspective. Front. Med.

Kathryn Eastwood, Alison Johnson, Angela Jones, Peter Cameron, Helena Teede, 857, Data harmonisation of Australian and New Zealand ambulance service datasets, International Journal of Epidemiology, Volume 50, Issue Supplement_1, September 2021, dyab168.184,

Enticott, Johnson, Teede. Learning Health Systems translating data-driven research into healthcare: A systematic review. BMC Health Services Research.

Melder, A., Robinson, T., McLoughlin, I., Iedema, R. and Teede, H. (2020), An overview of healthcare improvement: unpacking the complexity for clinicians and managers in a learning health system. Intern Med J, 50: 1174-1184.

Enticott, J., Braaf, S., Johnson, A. et al. Leaders’ perspectives on learning health systems: a qualitative study. BMC Health Serv Res 20, 1087 (2020).

Enticott, J., Johnson, A., Jones, A., Teede, H. (2020), Co-Designing a Learning Health System Framework: Learning Health Systems: Learning together for better health.

Teede, H.J., Johnson, A., Buttery, J., Jones, C.A., Boyle, D.I., Jennings, G.L. and Shaw, T. (2019), Australian Health Research Alliance: national priorities in data‐driven health care improvement. Med. J. Aust., 211: 494-497.e1.

Digital Health Training

Victoria

La Trobe University 

Offer both Graduate Certificate in Digital Health and a Master of Digital Health degree courses

Melbourne University

Their Centre for Digital Transformation of Health offer a number of short courses as well as a Graduate Certificate in Health Informatics and Digital Health

RMIT

Provides a number of Health Transformation courses and degrees, one of which is the Graduate Certificate in Digital Health.

Monash University

Provides a number of integrated digital health training opportunities through other degrees. The Fundamentals of Digital Health is a fully-online credential exploring the intersection between health and technology.

Monash University - Data Science: Data Driven Decision-Making Micro Credential

Monash University Libraries

The library also has useful resources for managing research data.

National

ANDHealth
Their mission is to build a world-leading, integrated ecosystem for the development, commercialisation and implementation of evidence-based digital health technologies in Australia. This will create a growth sector which delivers highly skilled jobs, creates economic opportunity and delivers health outcomes for all Australians

Australian Research Data Commons (ARDC) 
Supports a number of webinars that may be of interest. An example of these webinars is the Data Linkage series that was led by the Australian Clinical Trials Alliance (ACTA) and the Population Health Research Network (PHRN).

The four-part series focused on:

• Designing Clinical Trials using Linked Data
• Accessing Linked Data
• Ethical considerations in using Linked Data
• Accessing MBS and PBS data

For further information visit the ARDC data linkage webinar series.

Certified Health Informatician Australasia (CHIA) 
Is a unique credentialing program for health informatics. The CHIA credential demonstrates that candidates meet the Health Informatics core competencies to perform effectively as a health informatics professional in a broad range of practice settings.

Digital Health CRC: Webinars 
A series of Webinars are available on a number of topics. They can be accessed live or retrospectively.

Sydney University: MOOC 
has developed a free Massive Open Online Course (MOOC) with input from our translation research centres. 
The MOOC has been co-designed by stakeholders and subject matter experts from:

• Government Organisations
• Non-Government Organisations

To develop quality learning materials, initially, for foundational level digital health capabilities. 
It includes four capability domains:

1. Digital Technologies, Systems and Policies
2. Clinical Practice and Applications
3. Data Analysis and Knowledge Creation
4. System and Technology Implementation

Further details available, HERE 

Important to know

Monash Data Futures Institute
Monash Data Futures Institute brings together leading cross-disciplinary expertise, international partnerships and a large affiliate network. Using data-driven AI, we are enhancing health sciences, governance and policy and sustainable development – and empowering more agents of positive change.

Australian Institute of Digital Health (AIDH)
AIDH is Australasia’s peak body for digital health representing a united and influential single voice for health informatics and digital health leaders and practitioners.

Australian Health Research Alliance (AHRA) - Transformational Data Collaboration
Health services generate and collect huge amounts of data, however, the ability to use this clinical data for research is severely limited due to a lack of data integration nationally. This collaboration will uplift the use of clinical data for research across the country and engage national partners to support a consistent strategy in advancing Health Data Science.

Research Data Alliance (RDA)This international group of experts have developed COVID data sharing guidelines. These are aimed to help stakeholders follow best practices to maximise the efficiency of their work, and to act as a blueprint for future emergencies.  The recommendations in the document are aimed at helping policymakers and funders to maximise timely, quality data sharing and appropriate responses in such health emergencies.

Australian Government open data
A central source of Australian Government open data, with more than 80,000 datasets currently available.

#Datasaveslives
The toolkit aims to equip patient groups and health influencers with the information and materials they need to have a positive dialogue with their communities about health data and to potentially launch their own health data initiatives.

The International Consortium for Health outcomes measurement (ICHOM)
ICHOM brings together patient representatives, leading physicians and registry leaders to prioritise a core set of outcomes for different medical conditions. These are published in open-access Standard Sets.

Office of the National Data Commissioner (ONDC)– Data Sharing Principles
The Office supports the National Data Commissioner who is responsible for overseeing the DATA Scheme to:

• Serve the public interest by promoting better availability of public sector data
• Enable the sharing of public sector data consistent with the Privacy Act 1988 and appropriate security safeguards
• Enhance integrity and transparency in sharing public sector data
• Build confidence in the use of public sector data, and
• Establish institutional arrangements for sharing public sector data.

Information about the Five-Safes Framework is available through the Australian Bureau of Statistics

The Department on the Prime Minister and Cabinet also has Data Sharing Principles.

The Australian Government has committed to implementing a simpler, more efficient data sharing and release framework by establishing:

• A new Commonwealth Data Sharing and Release Act to streamline access and use of data; and
• A new National Data Commissioner to oversee the framework and legislation, and issue guidance and support to agencies to meet the new requirements.

The new Data Sharing and Release Act will:

SNOMED International
Determines global standards for health terms, an essential part of improving the health of humankind.

Key initiatives under the Platform include:

• Graduate Research Industry Partnership: The Digital and Data-Driven Innovation in Healthcare GRIP, a partnership between Monash University and the Monash Partners health services, where a cohort of 11 PhD students are addressing healthcare problems through digital and data-driven innovations and building their skills as the next generation workforce in this field
• The development of data sharing principles to support the safe, lawful and efficient sharing of data for healthcare improvement across our member organisations

• Development of the Monash Partners Learning Health Systems to guide improvement in health outcomes through better use of health and related data.

Monash Partners is proud to support the following prioritised projects:

2020

Developing health data research innovation hubs, integrating data experts/researchers into health settings to enhance data-driven healthcare and improve health outcomes
Dr Joanne Enticott and Alison Johnson

Developing Monash Partners wide visual representation models for data (data dashboards) for clinicians, managers and consumers, to better access and utilise clinical and/or registry data
Lauren Lawlor and Lavinia Tran

• Clinical and quality data that is available at the point of care and easy to visualise is an essential component of high-performing healthcare teams. Dashboards have historically been utilised within the business sector as tools to guide decision making. They are now gaining popularity in healthcare in order to display complex information through easily understood graphs, tables and images. Increasingly, dashboards are integrated into electronic medical records and used to portray operational activity and present clinical data within and across health services. Ms Lauren Lawlor and Dr Lavinia Tran, have explored the use of data dashboards across Monash Partners and identified an easy to use evidence-based methodology to guide the development of data dashboards in healthcare and clinical registry settings. They undertook a co-design approach that included a review of the literature, qualitative interviews with key stakeholders, including experts within business intelligence (BI) and/or clinical informatics units across our health partners. The strategies utilised included: peer reviewed literature which reported measurable improvements, expert opinion and stakeholder input, combined with several case studies, which led to a co-designed product. The purpose of the project titled Visual representation models to improve access and utilisation of health data: clinical dashboards across Monash Partners was to explore the use of data dashboards across Monash Partners and identify an easy to use evidence-based methodology to guide the development of data dashboards in healthcare and clinical registry settings. For more on data dashboards or to access a copy of the Visual representation models to improve access and utilisation of health data: clinical dashboards across Monash Partners report contact Ms Alison Johnson via email

Developing a strategic approach to Natural Language Processing (NLP) across Monash Partners health services
David Ung (from September 2020)

Developing a data harmonisation road map to improve maternal health outcomes
Dr Negar Naderpoor

2019 

The following projects were funded through a Medical Research Future Fund grant to Monash Partners.

Developing health data research innovation hubs, integrating data experts/researchers into health settings to enhance data-driven healthcare and improve health outcomes
Dr Joanne Enticott and Alison Johnson

Data linkage to provide near real-time monitoring of cardiac surgical performance – a local pilot for a national process
Adjunct Clinical Professor David Pilcher

Innovative use of AI for antifungal stewardship in patients with blood cancer
Dr Michelle Ananda-Rajah

Developing a data harmonisation road map to improve maternal health outcomes
Dr Negar Naderpoor

Development of a data harmonisation road map to inform linkage of prehospital and emergency department data
Dr Kathryn Eastwood

 2018 

Victorian Obstetric Anal Sphincter Injury (OASIS) Quality of Care Improvement Project
Associate Professor Sue Evans

Using Linkage to Reduce Avoidable Hospitalisation (ULTRA-GP)
Professor Danielle Mazza

Lung Cancer Clinical Quality Registry: a state-wide approach to monitoring and improving lung cancer care (HREC/16/ Alfred/84)
Professor John Zalcberg