Congrong Zhang, Aloha Ambe, Ben Matthews
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(https://doi.org/10.55612/s-5002-068-002)
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Abstract
Experience-Based Co-Design (EBCD) is a participatory approach commonly used to improve healthcare services. However, its application in guiding the design of technologies, particularly artificial intelligence (AI) systems, remains limited. This study adapts EBCD to support nurse-centered design of AI-enhanced electronic health records (EHRs) for patient handover. Drawing on interviews and co-design activities with nurses, AI experts, and UX designers in Australia, we identified workflow misalignments and co-developed AI features that address clinical challenges. Based on these findings, we propose a tailored EBCD approach for AI design, comprising five guiding elements: Scenario Co-Construction, Experience-Based Facilitation, Technical Feasibility Alignment, Design Integration, and Common Adjustment. This approach is aimed at promoting equitable participation, grounding design in real-world experience, and ensuring AI tools align with clinical workflows. Our work contributes a technology design pathway that builds on an established method and centers frontline clinicians as equal partners in shaping AI-integrated healthcare systems.
Keywords: Experience-Based Co-Design, EBCD, Patient handover, Electronic health record, EHR, Co-design, Nurses’ perspectives.
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Summary generated by AI
The paper argues that AI-enhanced electronic health records should not be designed mainly from a technical or vendor-driven perspective. Instead, AI support tools for nursing handover should be shaped through nurses’ lived experience, using an adapted Experience-Based Co-Design (EBCD) approach.
The goal is not just to add AI into healthcare systems – it is to make AI fit real clinical work, support safer handovers, and preserve nurses’ professional judgment.
1. Why current AI/EHR design is misaligned ?
The authors argue that many healthcare AI tools fail because they do not match frontline workflows.
Electronic health records are already central to nursing handovers, but nurses often face information overload, fragmented documentation, difficulty finding key details quickly, and time pressure during shift transitions.
The critique: AI tools are often introduced as technical solutions before designers fully understand the practical, emotional, and responsibility-heavy nature of nursing work.
2. What is Experience-Based Co-Design (EBCD)?
EBCD is a participatory healthcare design method that starts from people’s real experiences.
It gathers stories, identifies critical moments or “touchpoints,” and uses these insights to redesign services collaboratively.
In this paper, EBCD is extended beyond service improvement and applied to AI technology design. The key idea is that nurses should not simply validate pre-made AI systems; they should help define the problems, priorities, and design directions from the beginning.
So “co-design” means shared authorship, not late-stage feedback.
3. Study approach
The paper uses a two-phase study:
• Phase 1: Interviews
The researchers interviewed 10 nursing professionals across Australian hospitals to understand handover practices, EHR use, pain points, and attitudes toward AI.
• Phase 2: Co-design workshop
They ran a 90-minute workshop with nurses, AI experts, and UX designers. Nurses shared workflow experiences, AI experts discussed technical possibilities, and designers helped turn ideas into low-fidelity interface concepts.
The process was deliberately structured so that nurses’ experiences came first, and AI features came later.
4. Main handover challenges identified
The authors identify three main challenges in nursing handovers:
• Information overload
Nurses must search through large amounts of patient data and dense clinical notes to find what matters most.
• Documentation challenges
Nurses need to create accurate, individualized care plans under time pressure, often using a mix of written notes, digital systems, and personal workarounds.
• Transfer of responsibility
Handover is not only information exchange; it is also the moment when responsibility for patient care moves from one nurse to another. Missing or unclear information can affect safety and accountability.
5. AI features co-designed with nurses
The workshop translated these challenges into practical AI design opportunities:
• Intelligent handover summary
AI could generate a concise one-page summary of the most relevant patient information, such as recent changes, medications, outstanding tasks, and new consults.
• Priority alerts
AI could highlight urgent risks, omitted tasks, or important changes so nurses do not miss critical information during busy shifts.
• Nurse feedback and control
AI should explain its suggestions and allow nurses to accept, reject, or correct them. The system should assist clinical judgment, not replace it.
6. Proposed EBCD approach for AI design
The paper proposes five guiding elements for adapting EBCD to AI-supported healthcare technology:
• Scenario co-construction
Use shared scenarios, such as videos or workflow examples, so nurses, designers, and AI experts build a common understanding.
• Experience-based facilitation
Start with nurses’ stories and pain points before discussing technology.
• Technical feasibility alignment
Bring AI experts in early so ideas are connected to what AI can realistically do.
• Design integration
Use sketches and prototypes to turn abstract ideas into concrete interface concepts.
• Common adjustment / collaborative prioritization
Refine ideas together, balancing clinical value, technical feasibility, safety, and implementation constraints.
7. Important warning
The authors caution against treating AI as the solution by default.
AI should not dominate nursing work, automate professional judgment, or add more burden to already complex workflows. It should serve clinical practice, trust, safety, autonomy, and patient care.
Main takeaway
The paper’s vision is that healthcare AI should be designed with frontline clinicians as equal partners, so that AI tools are not imposed on clinical work but carefully integrated into it.
In one sentence:
Move from “AI added to healthcare systems” to “AI co-designed with the people who actually deliver care.”
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