Aim: Reconstructive microsurgery places exceptional physical demands on surgeons — procedures routinely exceed sixteen hours, require sustained fine motor precision, and impose significant ergonomic strain through prolonged use of loupes, headlamps, and operating microscopes. Chronic work-related musculoskeletal pain affects up to 67% of microsurgeons, contributing to reduced quality of life, early career burnout, and a widespread perception that microsurgery is unsustainable into later career stages. This presentation examines how intentional ergonomic design — fitting the workplace to the surgeon — can protect both the practitioner and the longevity of the specialty.
Methods/Approach: Semi-structured interviews were conducted with microsurgeons across early, mid, and late career stages to capture lived experience of work-related pain, adaptive strategies, and how physical health has shaped surgical practice over time. Findings were complemented by a targeted literature review identifying established risk factors and evidence-based interventions for poor ergonomics in microsurgery.
Results: Cervical spine health emerges as the primary vulnerability, driven by sustained neck flexion from optical equipment and fixed operative positioning. Late-career surgeons who continue to perform microsurgery consistently attribute their longevity to intraoperative mobility, targeted physical conditioning, and deliberate equipment choices — including lighter headgear and technologies that support neutral head posture. Regular intraoperative breaks were also identified as a practical and underutilized protective strategy.
Discussion/Implications: Microsurgery offers a compelling case study in what happens when the work does not fit the worker. Embedding ergonomic awareness and physical conditioning into surgical training programs and hospital culture is not a peripheral concern — it is essential to surgeon wellbeing and workforce sustainability. For the HFE community, this work highlights opportunities to collaborate with surgical specialties where human-centered design is overdue.

Aim
Prescription drug monitoring programs (PDMPs) are clinical decision support systems that manage and mitigate certain high-risk medicine use and risks. SafeScript NSW is the statewide PDMP implemented in 2022 in New South Wales (NSW), Australia. This study examined the perceived impacts of SafeScript NSW from the perspective of healthcare practitioners.

Methods
This study used a qualitative descriptive design. Participants were prescriber and pharmacist users of the PDMP in NSW. Recruitment and data collection were completed May-August 2024. Semi-structured interviews were audio-recorded and transcribed. Thematic analysis was guided by the Quadruple Aim framework. Impacts were classified as those relating to 1) population health outcomes, 2) patient experience of care, 3) costs, and 4) practitioner experience of work.

Results
Fourteen interviews were conducted and analysed. PDMP’s perceived impacts on population health included improved medication safety and reduced prescription shopping. Key patient impacts included risk of stigma and treatment interruption. Despite these, both prescribers and pharmacists reported improved therapeutic relationships with patients following SafeScript NSW use. Impacts on relationships between healthcare practitioners were mixed, with resistance encountered from those who do not use SafeScript NSW. No impacts of PDMP on healthcare delivery costs were reported. Participants discussed efficiency impacts relating to practitioners’ work. Both practitioner groups reported PDMP use increased confidence and safer prescribing/dispensing practices. Workflow misalignment and workarounds were reported, predominantly by pharmacists.

Discussion/Implications
This study adds evidence on healthcare practitioners’ perspectives on PDMP. Participants perceived many positive impacts of SafeScript NSW use, including improved population health outcomes and patient care. To minimise negative impacts, we suggest further evaluation and strategies to address user-identified gaps, including workflow challenges. Collaborative development of system improvements and strategies with users can maximise continued user acceptance and uptake, benefits realisation, and the system’s long-term success.

Care at home models are expanding as health systems seek alternatives to traditional inpatient care. While these models are increasingly used for medical patients, extending post-operative care into the home introduces new human factors and systems design challenges. Surgical recovery depends on continuous monitoring, rapid escalation, interdisciplinary coordination, and patient engagement—functions traditionally supported by the hospital environment.

At our institution, we expanded a care at home program to include surgery patients co-managed by hospitalists. This required redesigning workflows to manage post-operative risks outside the hospital setting. Through iterative implementation, we developed condition-specific monitoring pathways, escalation protocols, and interdisciplinary communication processes to support safe transitions from hospital to home.

This work exposed important cognitive and organizational challenges, including defining which patients are appropriate for care at home, managing clinical uncertainty with distributed teams, balancing patient autonomy with safety, and adapting hospital-based workflows to home environments not designed for clinical surveillance.

This lightning talk will explore how extending surgical recovery into the home transforms the relationship between patients, clinicians, technology, and care systems. We will discuss lessons learned from redesigning post-operative care workflows beyond the hospital and highlight opportunities for human factors approaches to improve safety, resilience, and coordination in emerging care at home models.

The incorporation of machine learning algorithms (a form of artificial intelligence (AI)) into medical devices and clinical decision support systems presents concerns relating to ethical use, algorithm validity / reliability, and data source transparency. Some researchers have suggested “model facts” labelling, as a potential solution (Sendak et al, 2020; Yoo et al., 2025). These labels are akin to nutrition or drug facts labels, but for machine learning algorithms.
One of the challenges with labels for machine learning algorithms, is that often they are designed by developers of the specific technologies. This means that there is little consideration of the end user requirements, such as what information is needed on a label from a clinician perspective, or how a label may effectively integrate into workflows that supports clinician cognitive functions without increasing cognitive demands (a known irony of automation and artificial intelligence).
My research aims to investigate how useful “model facts” labels may be to clinicians, and if they are, how best to integrate labels into clinical workflows. This is of particular importance in hospital / acute care settings, as these environments often place competing demands for cognitive resources on workers.
I plan to use cognitive task analysis (CTA) methods understand how clinicians currently conduct their work, and at what points of the work flow they would likely have cognitive capacity to incorporate crucial algorithm information into their clinical decision making. From CTA, we will be able to identify clinician’s key requirements for label integration into workflow and provide an overview of design considerations. We hope that this work will offer insights into “the perfect fit” between work-as-done and intended changes into clinical workflows.

Aim:
To answer; what digital interventions support antimicrobial medication management processes in RACHs, are they effective, and why?
Methods:
A scoping review was conducted in accordance with PRISMA-ScR guidelines. Studies were eligible if they described the use, evaluation, or implementation of a digital health intervention in RACHs that supported antimicrobial medication management. Study characteristics and key findings were extracted including the prevalence of digital intervention use, implementation factors (usability, acceptability, and end-user experiences), and antimicrobial-related outcomes.
Results:
Eleven studies were included. Studies were predominantly conducted in the United States (n=5) and used quantitative designs (n=8), including two RCTs. Digital interventions ranged from clinical decision support systems and electronic health records (EHR) to virtual antibiotic teams. Facility level use and access was high, however clinicians external to the RACH had ‘no access’ or ‘view only’ to facility data. Antimicrobial outcome findings were mixed; two studies reported statistically significant improvements in prescribing appropriateness, while reductions in total antibiotic use were largely non-significant. Implementation was commonly hindered by poor system integration, limited availability of real-time antimicrobial data, language and access barriers, and increased workflow burden. Enablers included perceived usefulness, feasibility, comprehensive training, and ongoing education.
Discussion/Implications:
Although EHR systems were widely implemented, they were primarily used for general documentation rather than antimicrobial stewardship (AMS) functions such as surveillance, and audit. Reliance on offsite prescribers, who frequently lack access to facility systems and onsite AMS expertise, constrained the ability of digital tools to support antimicrobial medication management in RACHs. Overall, barriers to digital AMS in RACHs appear to be predominantly system-level rather than due to staff resistance. Effective digital AMS in this setting requires human-centred design, improved interoperability, and sustained implementation support tailored to the aged care context.

Aim
During our participatory research to improve care for older adults in emergency departments (EDs), one study site implemented a novel model of care to manage the priority needs of residents of aged care facilities, avoiding unnecessary and unwanted admission to hospital. The innovation was so successful, executive leaders determined that the same innovation would be implemented in a second ED study site in the region. Complexity in health systems is characterised by non-linearity, emergence, adaption, uncertainty, dynamism, and co-evolution. The opportunity to gain insights into the implementation of the same innovation in a second ED study site in the same region amid this complexity was highly appealing. We undertook a process evaluation to 1) provide ED staff with preliminary findings to guide ongoing decision-making, and 2) generate a foundation for formative and summative outcomes.
Methods
As a single local instrumental case study, theoretical propositions relating to complexity guided the inquiry. Document and interview data was analysed using thematic and content analyses.
Results
Key informant (n=5), staff (n=6), patient (n=3), and carer (n=5) interviews showed the second ED was not as successful in achieving organisational outcomes due to contextual differences including: patient acuity profile; comprehensive community services; paramedic decision-making; and local staff constraints. Improvement in patient and ED staff experience was not transferrable to aged care staff. Adaptions to the innovation were being made, but exposed service gaps that must be addressed to manage an increasing older adult population. The slow pace of research was found to be a poor match for the rapid speed of innovation in healthcare that contributed to implementation without full understanding of context.
Implications
This case highlights important contextual factors that may negatively impact effort and investment in health service reform, and the need for more rapid research practices to meet health services' needs.

Key words: Musculoskeletal disorders (MSDs), participatory ergonomics, human-centred design, medical device

Context
Musculoskeletal disorders (MSDs) remain a leading cause of workplace injury in manufacturing, consistent with health and safety dashboard data from a medical device manufacturing company in New Zealand. Despite ergonomic assessments conducted prior to production line release, reports of pain and discomfort persisted, contributing to absenteeism and reduced productivity. This raised a critical question: why are workers still being injured? Over time, assessments had become a tick-box exercise rather than an effective means of managing risk.

Aim
This study examined the limitations of existing ergonomics tools and design practices to better understand the persistence of MSD risk.

Approach
The software tool used at the site evaluates tasks based on posture, exertion, movement, and exposure. Although useful, outputs are user-dependent and subject to variability; when applied in isolation, they do not sufficiently capture worker experience within the broader production system. In parallel, production line designers rely on generic anthropometric assumptions, which do not fully reflect workforce diversity or the dynamic nature of production. Guided by a commitment to continuous improvement, a participatory ergonomics strategy was developed, emphasising empathy, insight, and collaboration. Five steps were defined: identifying risks through health and safety data; co-designing with workers and stakeholders; treating ergonomic principles as a starting point; applying ergonomic assessment tools to support—not replace—professional judgment; and validating designs through real-world trials. These steps were formalised in an ergonomic guidance booklet and shared with design stakeholders.

Results and Implications
The framework offers a structured approach to integrating worker experience into design decisions. Future work will evaluate its impact on injury outcomes, system performance, and workforce engagement, and identify opportunities for broader organisational integration. Effective work design depends on ongoing collaboration among workers, design teams, and ergonomics specialists.