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Expert Report on Clinical Workflow Automation for Allied Health Professionals in Australia Google

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preface_schema: ‘1.0’ title: ‘Expert Report on Clinical Workflow Automation for Allied Health Professionals in Australia: A Strategic Curriculum Blueprint’ source_type: ‘Consulting Company’ publisher: ‘Ey’ publishing_date: ‘2029’ authors: [‘I. Strategic Context’] available_at: ‘https://doi.org/10.3389/fpubh.2021.648009/full’ credibility_tier_value: ‘5’ credibility_tier_key: ‘peer-reviewed’ credibility_tier_label: ‘Peer-Reviewed’ credibility: ‘Final Peer-Reviewed Report’ keywords: [‘health’, ‘digital’, ‘clinical’, ‘allied’, ‘care’, ‘national’, ‘automation’, ‘ahps’] abstract: ‘Expert Report on Clinical Workflow Automation for Allied Health Professionals in Australia: A Strategic Curriculum Blueprint I. Strategic Context and the Australian Mandate for AHP Digital Transformation A. Defining the Allied Health Workforce and its Digital Role The Australian allied health sector represents a substantial and rapidly expanding segment of the nation’s healthcare system, currently comprising the second-largest clinical workforce nationwide.[1] Allied Health Professionals (AHPs) operate as university-qualified practitioners providing specialised diagnostic, technical, therapeutic, and direct health services across critical areas, including aged care, mental health, disability, and general health sectors.[2, 3]’

Expert Report on Clinical Workflow Automation for Allied Health Professionals in Australia: A Strategic Curriculum Blueprint

I. Strategic Context and the Australian Mandate for AHP Digital Transformation

A. Defining the Allied Health Workforce and its Digital Role

ofessionals in Australia: A Strategic Curriculum Blueprint

I. Strategic Context and the Australian Mandate for AHP Digital Transformation

A. Defining the Allied Health Workforce and its Digital Role

The Australian allied health sector represents a substantial and rapidly expanding segment of the nation’s healthcare system, currently comprising the second-largest clinical workforce nationwide.[1] Allied Health Professionals (AHPs) operate as university-qualified practitioners providing specialised diagnostic, technical, therapeutic, and direct health services across critical areas, including aged care, mental health, disability, and general health sectors.[2, 3]

AHPs are recognised as autonomous practitioners who collaborate effectively alongside doctors, nurses, and midwives to deliver holistic, person-centred care.[3] They play an essential role in the management of chronic disease and the improvement of community quality of life.[3] A cornerstone of their practice is adherence to a strong culture of evidence-based practice, robust clinical governance, and continuous professional development. To qualify as an allied health profession in Australia, a discipline must possess a defined core scope of practice, national entry-level competency standards, and university health sciences courses accredited at AQF Level 7 or higher.[2]

sion in Australia, a discipline must possess a defined core scope of practice, national entry-level competency standards, and university health sciences courses accredited at AQF Level 7 or higher.[2]

The adoption and use of clinical information systems (CIS) in the allied health sector are continually growing, aligning with the necessity for digital information as the foundation of high-quality healthcare.[4, 5] Digital transformation promises significant benefits for patients, including better coordination of care for those with chronic and complex conditions, reduced duplication of tests, and fewer adverse drug events.[5] For providers, the demand is clear: they require secure digital services that offer instant access to patient information and reduce administrative burdens, allowing them to allocate more time directly to patients.[5]

B. National Policy Drivers: The ADHA Strategy and the Allied Health Digital Uplift Plan

The Australian Digital Health Agency (ADHA) was established to steer the development and implementation of the National Digital Health Strategy, guiding the sector toward common goals for connected digital services.[5] A central component of this strategy for the AHP workforce is the National Allied Health Digital Uplift Plan.[1, 6]

This plan outlines a coordinated pathway to strengthen digital capability across the nation’s allied health workforce, ensuring AHPs can embrace the digital tools necessary for the shift toward a more digitally connected, collaborative, and data-driven system.[1, 7] The plan specifies four primary outcomes for allied health professions:

1. Digital readiness: Possessing the correct digital healthcare solutions, training, and infrastructure to deliver safe, efficient care.

2. Collaboration and integration: Achieving seamless connection into multidisciplinary care teams via secure, interoperable systems.

s, training, and infrastructure to deliver safe, efficient care.

2. Collaboration and integration: Achieving seamless connection into multidisciplinary care teams via secure, interoperable systems.

3. Data-driven practice: Utilising timely, high-quality information to inform clinical decisions and improve outcomes.

4. Person-centred care: Ensuring health information is centred around the consumer and flows seamlessly across settings.[7]

The long-term vision articulated in national policy (post-2029) explicitly requires that digital tools be seamlessly integrated into everyday workflows across diverse care settings.[7] Furthermore, AHPs are expected to be connected to the national digital health infrastructure, actively using electronic referrals and requests, and engaging in health information exchange. This future state includes the safe use of data for research and decision-making, supported by AI tools and other emerging technologies for contemporary and personalised care.[7]

The necessary training regarding Clinical Workflow Automation (CWA) must be framed not merely as a technical upskilling opportunity but as a fundamental professional obligation. The national priority has elevated digital capability from a competitive advantage to a required component of compliant, multidisciplinary care. Successful engagement with CWA technologies, such as electronic referrals (e-referrals) and AI support, is explicitly designated as mandatory for AHPs to participate actively in the national health information exchange by the policy timeline.[7]

such as electronic referrals (e-referrals) and AI support, is explicitly designated as mandatory for AHPs to participate actively in the national health information exchange by the policy timeline.[7]

However, the realization of this collaborative vision is currently constrained by technical realities. Despite the policy goal of universal e-referral adoption, a significant barrier remains the inability for secure message services to seamlessly communicate data from one platform to another.[8] This issue of interoperability represents a fundamental technical bottleneck in Australia’s digital infrastructure. Therefore, effective CWA training must equip AHPs with a nuanced understanding of interoperability standards, such as Fast Healthcare Interoperability Resources (FHIR®) and SNOMED CT.[9] This training should empower AHPs to recognise and troubleshoot interoperability failures, allowing them to function as active advocates for systemic improvements in their capacity as change agents (aligning with Domain 4 of the capability framework).

II. Principles and Practical Applications of Clinical Workflow Automation (CWA)

A. Conceptualizing CWA: Efficiency, Safety, and the Therapeutic Relationship

Clinical Workflow Automation (CWA) involves applying technology to streamline healthcare processes, significantly reducing administrative burden and enabling clinicians to dedicate greater focus to patient care, thereby protecting the core therapeutic relationship.[10, 11] The implementation of CWA is positioned as a critical strategy to mitigate the pressures on healthcare systems resulting from an aging population, rising chronic disease prevalence, and workforce shortages.[12]

entation of CWA is positioned as a critical strategy to mitigate the pressures on healthcare systems resulting from an aging population, rising chronic disease prevalence, and workforce shortages.[12]

The value proposition of CWA extends beyond mere time savings. Benefits include cost reduction through the automation of manually-intensive processes, improved job satisfaction, elevated employee retention rates, and decreased risk of error.[11, 13] Automation provides enhanced accuracy in data recording and analysis, reducing omissions and inaccuracies often associated with overburdened clinicians.[11] Although the implementation of digital health technologies, including AI, can initially be disruptive, it has proven useful for improving work productivity, optimising clinical workflow, reducing risk, and augmenting clinical decision-making.[14]

B. Primary Domains for AHP Workflow Automation (Indirect Clinical Tasks)

CWA primarily targets indirect clinical tasks—those administrative and operational processes that consume significant professional time but do not involve direct therapeutic intervention.[10, 15]

  1. Automating Clinical Documentation The most widely discussed application of CWA in clinical settings is automated documentation, particularly through Artificial Intelligence (AI) scribes. AI scribes, also referred to as ambient AI scribes or digital scribes, are tools that automate portions of the documentation process by converting patient conversations into clinical notes, summaries, or letters for incorporation into the patient’s health record.[16]

, are tools that automate portions of the documentation process by converting patient conversations into clinical notes, summaries, or letters for incorporation into the patient’s health record.[16]

• Efficiency Gains: There is limited but emerging positive evidence that AI scribes, or speech recognition, can automate documentation tasks and free up clinician time, leading to increased efficiency, including a reduction in the time taken to complete clinical notes and an increase in the number of patients seen.[10, 13] Australian hospitals, including those in Queensland and South Australia, have commenced trialling endorsed AI scribes in outpatient settings, sometimes integrating them directly with the electronic health record (EHR).[10]

• The Productivity Paradox: Despite claims that Large Language Model (LLM)-based systems shorten documentation time, research indicates that studies often rely on small sample sizes or single-site data, which limits generalisability.[10] Crucially, any time savings gained from auto-drafting can be partially negated by the necessary human-editing time required for critical review and correction.[10] This creates a verification burden, shifting the cognitive effort from writing the note to critically appraising the AI’s output against the patient encounter to ensure accuracy and concordance.

  1. Streamlining Referrals and Communication Electronic referrals (e-referrals) are secure electronic letters transmitted between healthcare professionals and are essential for multidisciplinary care coordination.[8] Australian digital health initiatives, such as the expanded Allied Health Industry Offer, actively support the co-development and delivery of eHealth solutions focused on secure messaging, My Health Record connectivity, and electronic prescribing for key AHPs like physiotherapists, psychologists, speech pathologists, and dietitians.[17]

of eHealth solutions focused on secure messaging, My Health Record connectivity, and electronic prescribing for key AHPs like physiotherapists, psychologists, speech pathologists, and dietitians.[17]

  1. Administrative and Logistics Management Workflow automation is a game-changer for administrative logistics, including efficient inventory management, order processing, and smart scheduling.[11, 13] By automating the ordering process and providing real-time updates on inventory levels (e.g., medicines, equipment, and consumables), CWA helps healthcare organisations avoid stock shortages and reduce waste, leading to direct cost savings.[11] Automated reminders and smart scheduling systems also improve service delivery by minimising missed appointments.[13] For specific disciplines like physiotherapy, CWA can be applied to the triage and scheduling process to address non-attendance issues and long waiting times, thereby improving operational flow.[18]

C. Discipline-Specific Implementation Insights

The diverse nature of the AHP workforce, which spans over 27 professions [3], means that CWA adoption presents discipline-specific challenges and benefits.

  1. Physiotherapy Triage Automation Physiotherapy clinics often face significant non-attendance issues and long waiting lists, prompting investigations into new models of care.[18] In Australia, trials have focused on physiotherapist-led triage and treatment services supported by automated processes.[19] For example, automated triage can match patients to different modes of care based on risk (e.g., low, medium, or high risk of poor outcomes). Low-risk patients might receive simple advice and education, while medium-risk patients might be offered telehealth physiotherapy, demonstrating CWA’s role in optimising resource allocation and reducing waiting times.[19]

receive simple advice and education, while medium-risk patients might be offered telehealth physiotherapy, demonstrating CWA’s role in optimising resource allocation and reducing waiting times.[19]

  1. Occupational Therapy and Documentation Quality Research examining the use of AI in generating Occupational Therapy (OT) documentation has yielded important findings regarding the quality of automated outputs.[20] A study comparing licensed occupational therapists’ documentation with that generated by ChatGPT-3.5 found that AI-generated notes were rated significantly higher across quality subdomains (completeness, correctness) and empathy dimensions.[20] However, the same study revealed that human-generated documentation demonstrated greater consistency and stronger inter-rater reliability among evaluators.[20] This highlights that while AI tools can potentially reduce documentation burdens by drafting high-quality, empathetic notes, human contextual sensitivity and consistency remain critical for clinical governance and reliability.

AI tools can potentially reduce documentation burdens by drafting high-quality, empathetic notes, human contextual sensitivity and consistency remain critical for clinical governance and reliability.

  1. Dietetics and System Rigidity For AHPs operating within large hospital systems, digital constraints can hinder the very standardisation CWA is meant to achieve. Interviews with clinical dietitians in Australian tertiary hospitals indicated that highly integrated electronic medical record (iEMR) systems often present rigid digital workflows.[21] This rigidity causes frontline clinicians to bypass structured templates, instead drafting notes in external software (such as Word) and pasting the content back into the iEMR to “make it look neater for everyone”.[21] These manual workarounds introduce variability, risking documentation standardisation and undermining the integrity of the supposed digital workflow. This systemic inflexibility demonstrates that the implementation of CWA cannot succeed solely through technical mandate; the course must empower AHPs to articulate system failures to IT and governance bodies, thus transforming them into active change agents (Domain 4) who can advocate for user-friendly, flexible digital tools.

III. The Foundational Curriculum: Aligning CWA with the Digital Capability Framework

To ensure that CWA training is relevant, effective, and nationally aligned, the curriculum must be anchored in the Digital health capability framework for allied health professionals.[22, 23] This Victorian-developed framework is widely accepted as the national standard, outlining the essential knowledge and behaviours required for safe and effective AHP practice across all therapies and science professions, from new graduates to leaders.[22]

A. Core Domains and Capability Progression

The framework identifies four core domains essential for AHP digital capability:

all therapies and science professions, from new graduates to leaders.[22]

A. Core Domains and Capability Progression

The framework identifies four core domains essential for AHP digital capability:

• Domain 1: The digital workplace: Focuses on safe and effective practice within a digital work environment, including technology use and troubleshooting.[22]

• Domain 2: Digital professionalism: Addresses the ethical, legal, and professional requirements of allied health practice in a digital context.[22]

• Domain 3: Data and informatics: Concerns the collection, collation, analysis, and application of data and knowledge to inform practice.[22, 24]

• Domain 4: Digital transformation: Involves using technology to transform and evaluate allied health services, practice, and models of care.[22]

AHPs progress through four capability levels, which describe increasing autonomy, task complexity, strategic awareness, and level of influence.[22] These levels are: Foundation (gaining experience), Consolidation (further skills and knowledge), Expert (applying and evaluating), and Leader (providing strategic guidance and proposing new concepts).[22]

B. Curriculum Mapping: CWA Focus Areas by Capability Level

The course curriculum for CWA must systematically map the required knowledge to these national standards, providing a criterion-based guide for educators.[22] This ensures that professional development aligns with nationally recognised milestones for advancement in digital practice.

CWA Curriculum Mapping to Digital Health Capability Framework

ucators.[22] This ensures that professional development aligns with nationally recognised milestones for advancement in digital practice.

CWA Curriculum Mapping to Digital Health Capability Framework

For AHPs progressing to Expert and Leader levels, the required digital capability extends beyond discipline-specific tools to encompass the broader interoperability required for integrated care.[3] Leaders must possess an in-depth understanding of interoperability standards, such as FHIR® training, and grasp the significance of clinical terminology (SNOMED CT) to drive effective national health information exchange.[9] This focus ensures that AHP leaders can contribute to and propose new ideas for system-level change, fulfilling their strategic guidance role.[22]

IV. Clinical Governance, Ethical Responsibility, and Risk Mitigation in Automated Practice

The integration of CWA, particularly AI-driven tools, introduces complex ethical, legal, and professional considerations that must be central to any training curriculum.[27]

A. Medicolegal Accountability and Human Judgment

A core principle governing the use of AI in clinical practice is the unwavering responsibility of the practitioner. Ahpra (Australian Health Practitioner Regulation Agency) guidelines are explicit: practitioners must apply human judgment to any output of AI.[25] The use of an AI tool, including AI scribes, does not diminish a clinician’s ultimate responsibility for the accuracy and relevance of the medical record.[16, 28]

n judgment to any output of AI.[25] The use of an AI tool, including AI scribes, does not diminish a clinician’s ultimate responsibility for the accuracy and relevance of the medical record.[16, 28]

Medical records are the primary evidence in medical negligence claims.[28] If an AI scribe makes an error—such as mishearing a key symptom, omitting a crucial detail, or misinterpreting language—and the clinician fails to identify and correct that error, the clinician may be held legally liable.[28] The law does not grant exception for mistakes simply because a machine initiated them. Consequently, the curriculum must dedicate a specific module to “Verification and Clinical Concordance,” training AHPs in specialised skills to rapidly and critically appraise AI outputs against the patient encounter.

Furthermore, organisations and practitioners must proactively ensure that any AI tool or software is rigorously tested and confirmed as “fit-for-purpose” before being deployed in clinical practice.[25]

B. Ethical Imperatives: Automation Bias and Workforce Resilience

The introduction of automation must be managed to mitigate cognitive and ethical risks.

  1. Managing Automation Bias: A primary risk is automation bias, which occurs when a clinician overly relies on or uncritically accepts the output of an automated system.[26] This bias can lead to two types of serious errors: errors of commission (acting on incorrect AI recommendations) or errors of omission (failing to notice something the AI missed).[26] AHPs must be trained to critically evaluate AI outputs, recognising that these technologies support, but do not replace, clinical judgment.[26]

mission (failing to notice something the AI missed).[26] AHPs must be trained to critically evaluate AI outputs, recognising that these technologies support, but do not replace, clinical judgment.[26]

  1. Addressing Workforce Anxiety and Deskilling: The implementation of AI raises concerns among AHPs regarding potential risks to professional practice and the replacement of their roles.[12] To address this resistance, the training narrative must proactively position CWA not as a displacement technology, but as a critical patient safety initiative and an augmentation tool.[14] Automation reduces human error associated with fatigue and stress [11], thereby freeing up capacity for AHPs to focus on complex, human-centric care and augmentation of clinical decision-making. Successful implementation requires targeted strategies based on behaviour change theory, including clear communication of benefits, workforce upskilling, and the use of local clinical champions.[12]

  2. Bias and Equity: Ethical practice demands that AHPs understand the inherent bias that can exist within the data and algorithms underpinning AI applications.[25] The curriculum must include content on ensuring the health and safety of Aboriginal and Torres Strait Islander people and all patients from diverse backgrounds, only using AI tools when appropriate to ensure equitable outcomes.[25]

C. Data Security, Privacy, and Informal Clinical Communication

All CWA adoption must strictly comply with Australian privacy laws, including the Privacy Act 1988.[22, 26] Data generated or transcribed by AI tools must be treated as sensitive health information, transmitted only via approved secure channels, and steps must be taken to destroy or de-identify personal information when it is no longer needed.[26]

must be treated as sensitive health information, transmitted only via approved secure channels, and steps must be taken to destroy or de-identify personal information when it is no longer needed.[26]

  1. Requirements for Informed Consent: When using AI scribing tools that record consultations, particularly those using generative AI (which often involve the input of personal data), AHPs must obtain and document informed consent from the patient.[25] Transparency is key: practitioners should advise patients how the AI supports care delivery, outlining its risks, limitations, and alternatives, ensuring the patient has the capacity to make a voluntary, informed decision.[26]

  2. Governance of Informal Communication: While policy efforts rightly focus on formal systems (e-referrals, EMRs), a major governance gap exists in Informal Clinical Communication (ICC).[29] Much communication between clinical and administrative staff occurs via ungoverned channels such as SMS, pagers, and encrypted messaging apps.[29] This ICC is often poorly audited and documented, leading to high levels of staff frustration, delay, interruption, and inefficiency.[29] The failure to govern ICC processes risks nullifying the safety and efficiency gains achieved through formal CWA, making ICC governance a vital component of Domain 2 training.

V. Pedagogical Design, Delivery, and Assessment Recommendations

The course on Clinical Workflow Automation must be designed for maximum applicability and retention within a diverse, working AHP population.

A. Course Structure and Foundational Modules

The course should utilise a flexible, asynchronous, and interactive modular format to align with professional development requirements.[30] It should cover foundational concepts necessary to contextualise CWA, including:

• Definitions of Digital Health, Digital Medicine, and Digital Therapeutics.[30]

• An introduction to Learning Health Systems and Electronic Health Records (EHR).[31]

extualise CWA, including:

• Definitions of Digital Health, Digital Medicine, and Digital Therapeutics.[30]

• An introduction to Learning Health Systems and Electronic Health Records (EHR).[31]

• In-depth focus on CWA technologies: Telehealth, remote monitoring, mobile applications, AI, and Machine Learning.[30, 31]

• The legal, ethical, security, privacy, and confidentiality concerns specific to digital health approaches.[32]

• Case studies demonstrating both successful and failed digital health implementations.[31]

The curriculum should be aligned with national policies, such as the National Allied Health Digital Uplift Plan [6], and should aim for professional development recognition or Continuing Education Units (CEUs).[9, 30] Furthermore, CWA should be presented as the logical and necessary evolution of existing digital practice, capitalizing on the established comfort AHPs have gained through widespread adoption of telehealth during recent years.[33, 34]

B. Recommended Pedagogy: Integrating Simulation-Based Education (SBE)

Simulation-Based Education (SBE) is a highly effective method for teaching complex clinical and interprofessional skills to AHPs.[35] To ensure practical competency in CWA, SBE should be mandated for high-risk areas:

  1. Automation Bias and Error Detection Simulation: SBE scenarios must intentionally test the AHP’s ability to detect errors.[26] This involves simulating patient consultations where the AI scribe mishears a critical symptom (an error of commission) or omits key historical information (an error of omission). The AHP’s subsequent performance is assessed on their capacity to detect the error in the transcribed note and manually correct it before saving the clinical record.[36]

tion (an error of omission). The AHP’s subsequent performance is assessed on their capacity to detect the error in the transcribed note and manually correct it before saving the clinical record.[36]

  1. Secure Workflow and Interoperability Practice: Simulations must involve end-to-end CWA processes that test system competency. This includes practicing the process of sending a secure e-referral to an external party, verifying the recipient’s secure messaging service is connected, and ensuring the referral contains the requisite structured data (e.g., specific clinical coding or standardised terminology) to facilitate seamless care transition.[9, 17]

  2. Practicing Informed Consent and Transparency: Role-playing scenarios are vital for practising the sensitive task of obtaining informed consent for generative AI use.[25] AHPs must practise transparently explaining the risks and limitations of the AI scribe to the patient, ensuring they meet the conditions for voluntary, informed consent, and documenting the patient’s response in the health record.[25, 26]

C. Overcoming Barriers and Competency Assessment

The successful adoption of CWA hinges on addressing known barriers, particularly AHPs’ concerns about lack of AI knowledge, trustworthiness, and organizational readiness.[12] Training programs must integrate strategies based on behaviour change theory, using clinical champions and communicating the benefits clearly to counter resistance.[12]

Competency Assessment: Evaluation must move beyond traditional knowledge checks to assess the practical application of CWA skills.

• Criterion-Based Assessment: Assessment methods must be criterion-based, evaluating the AHP’s performance against the specific capability statements defined for the Foundation, Consolidation, Expert, and Leader levels across all four domains.[22]

s must be criterion-based, evaluating the AHP’s performance against the specific capability statements defined for the Foundation, Consolidation, Expert, and Leader levels across all four domains.[22]

• Validated Tools: Formal assessments should utilise scientifically validated digital health competency frameworks that measure specific secondary indicators, such as digital protection ability, health information acquisition ability, and the ability to screen and appraise health information.[37, 38] This ensures a comprehensive evaluation of practical digital health literacy, addressing the complexity of automation risk.

VI. Conclusion and Recommendations

Clinical Workflow Automation (CWA) is an essential component of the Australian health system’s digital future, moving rapidly from an optional efficiency enhancement to a core professional requirement for AHPs. The analysis confirms that successful integration of CWA is mandated by national policy, specifically the ADHA’s National Allied Health Digital Uplift Plan, which envisions AHPs as digitally connected, integrated, and data-driven practitioners by 2029.[7]

However, the efficacy of CWA depends on successfully navigating significant challenges related to clinical governance and system design. The core risk is not technical failure, but the erosion of professional standards due to automation bias and uncritical acceptance of AI outputs, which heightens the practitioner’s medicolegal liability.[26, 28] Furthermore, systemic barriers, such as the rigidity of current iEMR templates and the interoperability failures in secure messaging, actively undermine standardisation and force high-risk, non-compliant workarounds.[8, 21]

Key Recommendations for the Digital Health Course Curriculum:

interoperability failures in secure messaging, actively undermine standardisation and force high-risk, non-compliant workarounds.[8, 21]

Key Recommendations for the Digital Health Course Curriculum:

1. Mandate Capability Alignment: The curriculum must be structured using the Digital health capability framework for allied health professionals, mapping all CWA topics to the four domains and four capability levels (Foundation to Leader) to ensure professional recognition and career development alignment.[22]

2. Shift Focus to Verification and Governance: Training must emphasize the “Verification and Clinical Concordance” module over pure documentation speed. This addresses the legal burden on AHPs to critically verify AI scribe output and mitigates automation bias (Domain 2).[10, 26]

3. Integrate Simulation for High-Risk Tasks: Utilise Simulation-Based Education (SBE) to practice the detection of AI errors, the successful implementation of secure e-referrals, and the transparent process of obtaining informed consent for generative AI tools.[25, 36]

4. Promote AHPs as Change Agents: At Expert and Leader levels, the curriculum must provide expertise in data standards (FHIR®, SNOMED CT) and clinical informatics to empower AHPs to advocate for better system usability and interoperability, directly addressing system rigidity and promoting digital transformation (Domain 4).[9, 21]

5. Address Informal Communication Governance: Expand Domain 2 (Digital Professionalism) to include the governance requirements for Informal Clinical Communication (ICC), ensuring that communications via messaging apps are securely managed and documented to prevent gaps in the clinical record and maintain safety.[29]

1. Allied health workforce set for digital uplift across Australia, https://www.digitalhealth.gov.au/newsroom/media/allied-health-workforce-set-for-digital-uplift-across-australia

1. Allied health workforce set for digital uplift across Australia, https://www.digitalhealth.gov.au/newsroom/media/allied-health-workforce-set-for-digital-uplift-across-australia

2. What is allied health?, https://www.ahpa.com.au/what-is-allied-health

3. Allied health workforce, https://www.health.vic.gov.au/health-workforce/allied-health-workforce

4. Allied Health Digital Readiness Issues Paper [Word, https://www.health.gov.au/sites/default/files/2023-12/allied-health-digital-readiness-issues-paper.docx

5. Australia’s National Digital Health Strategy - Safe, seamless and secure, https://www.digitalhealth.gov.au/sites/default/files/2020-11/Australia%27s%20National%20Digital%20Health%20Strategy%20-%20Safe%2C%20seamless%20and%20secure.pdf

6. National Allied Health Digital Uplift Plan, https://www.digitalhealth.gov.au/about-us/strategies-and-plans/national-allied-health-digital-uplift-plan

7. ADHA releases allied health digital uplift plan | Health Services Daily, https://www.healthservicesdaily.com.au/adha-releases-allied-health-digital-uplift-plan/37794

8. eReferrals Why are we still faxing - RACGP, https://www1.racgp.org.au/ajgp/2018/january-february/ereferrals-why-are-we-still-faxing-1

9. Standards Academy - Australian Digital Health Agency, https://www.digitalhealth.gov.au/digital-health-standards/standards-academy

10. AI: automating indirect clinical tasks and administration: Living evidence, https://aci.health.nsw.gov.au/statewide-programs/critical-intelligence-unit/artificial/automating-indirect-clinical-tasks

11. Healthcare Workflow Automation - Adecco Australia, https://www.adecco.com/en-au/news-and-resources/maximising-efficiency-and-productivity-in-healthcare-the-role-of-workflow-automation

12. Overcoming barriers and enabling artificial intelligence adoption in allied health clinical practice: A qualitative study - PMC - NIH, https://pmc.ncbi.nlm.nih.gov/articles/PMC11792011/

omation

12. Overcoming barriers and enabling artificial intelligence adoption in allied health clinical practice: A qualitative study - PMC - NIH, https://pmc.ncbi.nlm.nih.gov/articles/PMC11792011/

13. The Transformative Power of Al in Allied Health Care - Smart Solutions Rehab Group, https://www.ssrg.com.au/blog/the-transformative-power-of-al-in-allied-health-care/

14. Allied Health Professionals’ Perceptions of Artificial Intelligence in the Clinical Setting: Cross-Sectional Survey - PMC - NIH, https://pmc.ncbi.nlm.nih.gov/articles/PMC11730220/

15. Identifying Opportunities for Workflow Automation in Health Care: Lessons Learned from Other Industries - PubMed Central, https://pmc.ncbi.nlm.nih.gov/articles/PMC8318703/

16. Artificial intelligence (AI) scribes - RACGP, https://www.racgp.org.au/running-a-practice/technology/artificial-intelligence-ai/artificial-intelligence-ai-scribes

17. Medical-Objects Joins ADHA’s $2M Allied Health Digital Initiative, https://www.medicalobjects.com/medical-objects-proudly-participating-in-national-allied-health-digital-health-initiative/

18. Cost of physiotherapy non-attendance at a metropolitan hospital in Australia: A time-driven activity-based costing study - PMC - NIH, https://pmc.ncbi.nlm.nih.gov/articles/PMC12104927/

19. Effectiveness of a physiotherapist-led triage and treatment service on WAITing time for adults with musculoskeletal pain referred to Australian public hospital physiotherapy clinics: a protocol for the WAIT-less trial - ResearchGate, https://www.researchgate.net/publication/388065207_Effectiveness_of_a_physiotherapist-led_triage_and_treatment_service_on_WAITing_time_for_adults_with_musculoskeletal_pain_referred_to_Australian_public_hospital_physiotherapy_clinics_a_protocol_for_the

20. Artificial intelligence in occupational therapy documentation: Chatbot vs. Occupational Therapists - PMC - NIH, https://pmc.ncbi.nlm.nih.gov/articles/PMC12515345/

apy_clinics_a_protocol_for_the

20. Artificial intelligence in occupational therapy documentation: Chatbot vs. Occupational Therapists - PMC - NIH, https://pmc.ncbi.nlm.nih.gov/articles/PMC12515345/

21. ‘Making the System Work’: A Multi-Site Qualitative Study of Dietitians’ Use of iEMR to Support Nutrition Care Transitions for Older Adults with Malnutrition - NIH, https://pmc.ncbi.nlm.nih.gov/articles/PMC12428660/

22. Digital health capability framework for allied health professionals - Health.vic, https://www.health.vic.gov.au/sites/default/files/2021-12/digital-health-capability-framework-for-allied-health-professionals.pdf

23. The Digital health capability framework for allied health professionals | health.vic.gov.au, https://www.health.vic.gov.au/digital-health/the-digital-health-capability-framework-for-allied-health-professionals

24. Evaluating digital competencies for allied health professionals in the United Kingdom - NIH, https://pmc.ncbi.nlm.nih.gov/articles/PMC10196533/

25. Meeting your professional obligations when using Artificial Intelligence in healthcare - Australian Health Practitioner Regulation Agency, https://www.ahpra.gov.au/Resources/Artificial-Intelligence-in-healthcare.aspx

26. AI Clinical Use Guide - Australian Commission on Safety and Quality in Health Care, https://www.safetyandquality.gov.au/sites/default/files/2025-08/ai-clinical-use-guide.pdf

27. Opportunities, Challenges, and Future Directions for the Integration of Automation in Nursing Practice: Discursive Study - PubMed Central, https://pmc.ncbi.nlm.nih.gov/articles/PMC12352802/

28. AI in healthcare: How digital scribes could rewrite medical negligence law in Australia, https://lawyersalliance.com.au/Web/Web/News/Opinion-Articles/2025/AI-in-healthcare-How-digital-scribes-could-rewrite-medical-negligence-law-in-Australia.aspx

rite medical negligence law in Australia, https://lawyersalliance.com.au/Web/Web/News/Opinion-Articles/2025/AI-in-healthcare-How-digital-scribes-could-rewrite-medical-negligence-law-in-Australia.aspx

29. Technology-based challenges of informal clinical communication in an Australian tertiary referral hospital: a survey-based assessment of user perspectives - NIH, https://pmc.ncbi.nlm.nih.gov/articles/PMC12007053/

30. American Physical Therapy Association: Introduction to Digital Health & Digital Practice, https://learningcenter.apta.org/products/introduction-to-digital-health-digital-practice

31. Introduction to Digital health - Coursera, https://www.coursera.org/learn/introduction-to-digital-health

32. Digital Health - MEHP | UPenn - University of Pennsylvania, https://improvinghealthcare.mehp.upenn.edu/course/digital-health

33. Digital health implementation in Australia: A scientometric review of the research - PMC, https://pmc.ncbi.nlm.nih.gov/articles/PMC11558741/

34. How Australian Health Care Services Adapted to Telehealth During the COVID-19 Pandemic: A Survey of Telehealth Professionals - Frontiers, https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2021.648009/full

35. Sim Guide: Allied Health scenarios, templates and tips for simulation based education | HETI, https://www.heti.nsw.gov.au/resources-and-links/resource-library/sim-guide-allied-health-scenarios-templates-and-tips-for-simulation-based-education

36. AI in Healthcare Simulation Education and Training | Vertically Integrated Projects, https://uavip.arizona.edu/ai-healthcare-simulation-education-and-training

37. Developing a digital health competency assessment framework for public health services: a Delphi-AHP approach - Frontiers, https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1634261/full

gital health competency assessment framework for public health services: a Delphi-AHP approach - Frontiers, https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1634261/full

38. Assessment Tools for Measuring Health Literacy and Digital Health Literacy in a Hospital Setting: A Scoping Review - PMC - NIH, https://pmc.ncbi.nlm.nih.gov/articles/PMC10778720/

Table 1:

Framework DomainCWA Focus AreaFoundation (Gaining Experience)Consolidation (Further Skills)Expert (Applying & Evaluating)Leader (Strategic Guidance)
D1: Digital WorkplaceTechnology Utilisation (AI Scribes, e-Referrals)Identify and understand the range and function of approved digital tools (e.g., My Health Record, CIS).[4, 22]Independently operate CWA tools; optimise tool performance and resolve simple technical challenges.[22]Evaluate and select appropriate digital health technologies based on risk identification and clinical indication.[22]Propose new CWA concepts; provide strategic guidance on tool deployment and system integration.[22]
D2: Digital ProfessionalismLegal Accountability & ConsentRecognize the need for informed consent when using recording/AI tools, especially generative AI.[25]Apply Ahpra professional obligations, demonstrating human judgment over automated output.[25]Educate peers on mitigating automation bias (errors of omission/commission) and ensuring transparency.[26]Develop and contribute to local or national policies on the ethical, secure, and accountable use of AI in allied health.[22]
D3: Data & InformaticsData Quality & Structured CaptureUnderstand how standardised terminology (e.g., SNOMED) and structured data capture improve workflow.[9]Critically review automated documentation outputs for correctness and clinical concordance.[10, 20]Conduct small-scale data analytics (e.g., evaluating automation impact on time or outcomes) to inform pr

ally review automated documentation outputs for correctness and clinical concordance.[10, 20] | Conduct small-scale data analytics (e.g., evaluating automation impact on time or outcomes) to inform practice improvement.[22] | Integrate CWA data safely to inform decision-making, facilitate research, and improve care pathways nationally.[7] | | D4: Digital Transformation | Innovation & Implementation | Identify opportunities for workflow improvement using new digital tools (e.g., moving from fax to e-referral).[8, 22] | Participate in piloting and testing new digital tools within a team setting; manage change required by automated workflows.[22] | Lead digital implementation projects; mentor others in digital integration and change management.[22] | Evaluate the impact of CWA on service delivery and advocate for technology changes at national/local levels.[21, 22] |

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