Improving Prehospital Documentation and Acute Care Handover Through Clinician-Led Digital Design

Executive summary

Prehospital and emergency care environments operate under conditions of extreme time pressure, high cognitive load, and fragmented information flows. Although electronic medical records (EMRs) are now widely adopted within hospitals, documentation and data handover during the prehospital phase of care often remain partially paper-based, unstructured, or poorly integrated with downstream systems. These limitations create risks for patient safety, continuity of care, and system learning.

This case study describes lessons learned from clinician-led digital health work undertaken during the design and early testing of PulsEMR, a prehospital-focused electronic patient care record and structured clinical data capture tool. Rather than focusing on the technology itself, the case study examines broader, transferable insights relevant to public-sector organisations seeking to improve documentation quality, clinical governance, and quality improvement in high-acuity environments. The experience highlights the importance of workflow-aligned digital design, structured data capture, and incremental implementation approaches that prioritise governance and risk management.

Context: prehospital care as a system pressure point

Ambulance services and retrieval teams form a critical interface between community-based care and hospital acute services. Decisions made during the prehospital phase frequently influence downstream clinical pathways, yet the information available to receiving teams is often incomplete, delayed, or inconsistently captured. This challenge is not unique to any single jurisdiction and is commonly reported across public health systems.

In many settings, prehospital documentation relies heavily on free-text narratives or post-event data entry, particularly during high-acuity cases. While these narratives provide important clinical context, they are difficult to analyse, audit, or reuse for quality improvement purposes. Handover information may be fragmented across verbal communication, paper records, and electronic systems, increasing the risk of information loss during transitions of care. As a result, prehospital data are often under-utilised for governance, training, and system-level learning, despite their clinical importance.

Problem statement

From a clinical governance perspective, prehospital documentation represents a critical but under-developed data source. When information is unstructured, delayed, or inconsistently recorded, health services face reduced visibility of patient trajectories and limited capacity to audit adherence to clinical standards. This places additional cognitive and administrative burden on clinicians and constrains the ability of organisations to identify variation, risk, or opportunities for improvement.

The development of PulsEMR was informed by this gap. The central question was how to support prehospital clinicians with real-time, structured documentation that aligns with the realities of emergency care delivery, while remaining flexible, safe, and compatible with public-sector governance expectations. Importantly, the objective was not to replace existing hospital EMRs, but to strengthen the prehospital phase of care and improve continuity across the system.

Digital approach informed by PulsEMR development

The digital approach underpinning PulsEMR was clinician-led and problem-driven. Design decisions were informed by direct experience in emergency and critical care settings, with a focus on supporting clinical work rather than imposing additional administrative tasks. Documentation elements were mapped to real-world prehospital workflows, recognising that clinicians often document in short intervals between clinical interventions rather than in a linear or uninterrupted manner.

Structured data capture was prioritised for core clinical elements such as presenting complaint, physiological observations, key interventions, and timelines. This approach was intended to support audit, quality improvement, and system learning, while reducing reliance on retrospective data abstraction. At the same time, free-text input remained available to allow clinicians to record nuance, uncertainty, and contextual detail that cannot always be captured through structured fields. This balance was essential to avoid introducing risk through overly rigid documentation requirements.

The system was developed using a modular design, allowing individual components to be simulated, tested, and refined without requiring full operational deployment. This incremental approach supported early learning and reduced the risk associated with introducing new digital tools into high-acuity environments.

Governance, safety, and compliance considerations

Introducing digital documentation tools into prehospital care carries inherent clinical and organisational risk. For this reason, governance and safety considerations have been incorporated from the outset at the design stage. Work to date has been conducted in-silico, using simulated workflows and non-identifiable data models to explore system architecture, documentation structure, and governance alignment without exposure to live clinical environments. This approach reflects a deliberate risk-management strategy appropriate for high-acuity public-sector settings.

While structured data can enable analytics and system insight, the design has deliberately avoided prescriptive clinical instructions. Any decision-support capability is framed as contextual and informational only, with clinical judgement remaining central at all times. This positioning aligns with established guidance on clinical decision support systems and recognises the importance of maintaining professional accountability in emergency care.

The tool has been conceptualised as an enabler of existing clinical governance processes rather than a replacement for them. Structured documentation is intended to support clinical audit, incident review, and quality improvement activities, while remaining aligned with recognised documentation standards. Privacy and data protection considerations have been addressed through design assumptions based on data minimisation principles and clear separation between identifiable data required for clinical care and de-identified data intended for secondary use. These assumptions have been developed to be compatible with public-sector requirements for Data Protection Impact Assessments and information governance review.

At the current stage, the focus has been on defining governance requirements, safety boundaries, and evaluation criteria that would need to be satisfied prior to any operational use. In-silico development has been used to identify potential risks, information governance considerations, and workflow dependencies, informing how any future service-led testing might be structured. No claims are made regarding clinical effectiveness, usability, or workflow impact, all of which would require formal evaluation through staged, real-world implementation under appropriate governance oversight.

Early insights and observations

At the current stage, work has been undertaken entirely in-silico, without deployment into live clinical environments or user testing with operational services. As a result, no claims are made regarding clinical effectiveness, usability, or impact on handover quality. Instead, the development process has clarified a number of design and governance considerations that will inform any future evaluation.

In particular, the work has highlighted the theoretical value of structured, time-stamped documentation for improving consistency of data capture in high-acuity settings, while reinforcing the importance of preserving narrative flexibility to accommodate clinical nuance and uncertainty. The in-silico work has also helped identify key questions that would need to be tested in future service-led evaluations, including the effect of structured documentation on clinician workload, reliability of data capture under time pressure, and compatibility with existing handover practices.

From a governance perspective, this stage has been used to define the criteria and safeguards that would need to be satisfied prior to operational use. Any future assessment of benefits related to audit efficiency, quality improvement, or system learning would require staged implementation, formal user acceptance testing, and oversight through established clinical governance processes.

Lessons for public-sector health systems

Several transferable lessons emerge from this experience. Prehospital data play a critical role in patient safety, governance, and system learning, yet are often under-utilised. Clinician-led design improves both safety and acceptance of digital tools, particularly in high-risk environments. Structured data capture enables audit and quality improvement without necessarily increasing documentation burden when aligned with workflows. Incremental implementation approaches reduce risk and support trust, while pragmatic integration with existing systems is preferable to wholesale replacement.

Broader implications

As public health systems increasingly explore analytics and artificial intelligence, this experience highlights the importance of foundational digital capabilities. Without reliable, structured data captured at the point of care, more advanced analytical tools are unlikely to deliver safe or meaningful value. Prehospital care represents a significant opportunity for improvement, not through automation alone, but through thoughtful digital support that respects clinical realities and governance requirements.

Potential future role of analytics and AI

While the work described in this case study has focused on foundational digital documentation and governance alignment, future enhancements could include the use of analytics and artificial intelligence to support secondary uses of structured prehospital data. Any such capabilities would be contingent on reliable data capture, robust information governance, and formal service-led evaluation. Potential applications may include summarisation of clinical information for handover, identification of documentation completeness, or support for audit and quality improvement activities. Importantly, any future use of AI would be designed to augment, rather than replace, clinical judgement, with clear human oversight and accountability, consistent with public-sector expectations for safe and ethical use of AI in healthcare.

Conclusion

This case study illustrates how clinician-led digital design, informed by the development of PulsEMR, can support safer documentation, improved handover, and stronger clinical governance in prehospital care. For public-sector organisations, the key insight is not the adoption of a specific technology, but the value of aligning digital initiatives with real-world workflows, established governance frameworks, and risk-managed implementation strategies.

References

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