Critical Clinical Information Workforce Shortage
Clinical Information Modelling (CIM) provides the foundation for interoperability, enabling health information to flow across organisational boundaries while preserving its clinical meaning and safety. Without it, digital health infrastructure remains a collection of isolated systems speaking different dialects, unable to collaborate effectively in the delivery of patient care.
A review into Australia’s Clinical Information Modelling (CIM) ecosystem has found our workforce training capabilities remain largely undeveloped, so more formal and informal training, and the establishment of national standards, to re-establish Australia’s leadership in digital health and data standards is needed, urgently.
The Workforce Competencies and Gap Analysis for Clinical Information Modelling in Australia, a report by the Digital Health Cooperative Research Centre (DHCRC) and RMIT University, has found that the shortage of skilled CIM professionals has become a bottleneck that threatens to constrain Australia's digital health ambitions.
Australia has historically punched above its weight, taking a leadership role in developing the methodology that went on to directly influence the openEHR standards used across Europe and in parts of the NHS. Australia was also instrumental in the development of HL7 FHIR, which is fast becoming the dominant global standard for clinical data exchange.
More recently, in preparation for Australia’s adoption of HL7 FHIR, the national Sparked Program has developed Australia’s core data for interoperability (AUCDI), providing standardised representations of clinical information for clinical data exchange through HL7 FHIR.
However, this shift toward HL7 FHIR has occurred without corresponding investment in CIM-specific workforce development.
The report makes a series of 11 recommendations as a way for Australia to maintain sustainable digital health leadership, including the establishment of a National Clinical Information Modelling Framework; practice-based training in CIM embedded into universities and training provider curricular; and integrating CIM into existing digital health programs.
RMIT University is set to develop a CIM specific module for its Health Informatics Course – making it the first Australian university to create a dedicated formal learning unit centred on CIM.
Report co-author and academic supervisor, Associate Professor Dr Sonika Tyagi from RMIT University, said the challenge is that this workforce barely exists in Australia.
“Australia has the historical credibility, the technical foundations, and the national digital health ambition to become a leader in CIM workforce development,” Dr Tyagi said. “What we currently lack is the coordinated investment in training infrastructure, professional recognition, and governance capability that would translate that potential into practice.
“Expertise in clinical information modelling, particularly using consensus-based approaches like openEHR, is concentrated among a small number of specialists. There is no established career pathway, no widely recognised professional identity, and no systematic approach to training.
“The shortage of skilled professionals has become a bottleneck that threatens to constrain Australia's digital health ambitions.”
This workforce gap is not unique to Australia. Internationally, countries that have implemented openEHR-based clinical information systems have also confronted similar challenges.
Moreover, the nature of the work itself is evolving. Early clinical information modelling efforts focused primarily on creating individual data models, often led by technical specialists with clinical input. Contemporary approaches, reflected in programs like AUCDI and the Sparked- AU Program, emphasise consensus-building, multi-stakeholder governance, and the creation of reusable information assets that can support diverse use cases.
DHCRC CEO Annette Schmiede said that while identifying significant gaps in the clinical information modelling capability in Australia, the report identifies strategies for strengthening it.
“The report makes it clear that simply referring to clinical information models in digital health strategies is not sufficient on its own. The adoption of a common data model approach for underpinning the development of interoperability standards must be accompanied by investment in formal training infrastructure, professional recognition, governance frameworks, and educator capability,” Ms Schmiede said.
“For universities and training providers, this report articulates the competencies required and identifies opportunities to incorporate clinical information modelling into health informatics curricula. For government, it highlights a critical dimension of digital health workforce development that has received insufficient attention to date.”
Read the full report and recommendations here.