Designing a multi-role system for Radiation Safety & Responsibility in Radiotherapy

Defining how responsibility moves across roles and how machine state is tracked in Radiation Controlled Areas

https://radpass.co.uk

Problem Framing

Radiotherapy workflows rely on coordination between Radiographers, Physicists, and Engineers, but responsibility is often informal, unclear, and not tracked. This creates critical risks:

• Unclear ownership of machine state
• No reliable audit trail
• Breakdowns during handovers

There was no formal system. Responsibility and machine state were tracked manually, often inconsistently.

Radiotherapy workflows rely on coordination between Radiographers, Physicists, and Engineers, but responsibility is often informal, unclear, and not tracked. This creates critical risks:

• Unclear ownership of machine state
• No reliable audit trail
• Breakdowns during handovers

There was no formal system. Responsibility and machine state were tracked manually, often inconsistently.

My Role

Founding Product Designer (0→1)

Defined:
• Responsibility model across roles
• System logic linking ownership + machine state
• Interaction model across tablet (real-time) and admin (oversight)

Challenge:

• Make responsibility explicit across roles
• Track machine state reliably for safety and compliance

System requirements:

• One clear owner at all times
• Machine state reflects real-world use
• All transitions are traceable

Defining the system

There was no formal model linking roles, responsibility, and machine state. This logic existed only in manual workflows.

To make it explicit, I mapped how responsibility, roles, and machine state interact as one system.

There was no formal model linking roles, responsibility, and machine state. This logic existed only in manual workflows.

To make it explicit, I mapped how responsibility, roles, and machine state interact as one system.

Where the model breaks in practice

In practice, responsibility is passed manually between roles, creating gaps in ownership and traceability.

Responsibility breaks during handovers

Ownership becomes unclear during handovers
Transitions introduce delays in critical workflows
System state and responsibility fall out of sync

Roles and machine state were tightly coupled, but managed separately, leading to inconsistencies in both.

Key shift

From

responsibility is handed over →

responsibility is handed over —→

responsibility is claimed

Responsibility is no longer handed over. It is claimed in real time, directly linking ownership to machine state.

Testing the model

Tested:

Handover model → created blocked states when responsibility wasn’t accepted
Pending ownership → introduced delays and friction
Self-claim model → simplified workflows and reduced risk

This model redefined responsibility as a real-time action, not a transfer. It removed handover dependency, reducing delays and improving traceability.

The next step was designing how this system surfaces across two interfaces.

One system, Two interfaces

Clarifies ownership, reduces delays, and enables safe, auditable workflows across roles.

• Tablet → real-time actions in high-pressure clinical environments
• Admin → system-wide control, configuration, and auditability

Same system. Different surfaces.

Admin → System Control

• Configure roles and permissions
• Monitor machine states across areas
• Maintain audit logs for compliance

Tablet → Real-Time Operation

• Take responsibility for areas
• Update machine state in real time
• Perform actions on-site

Eliminating Handover: Designing for Ownership

Tested different models to define how responsibility should work in practice.

1

Push Model

Initial workflows relied on handovers between roles.

This created blocked states, unclear ownership, and delays in high-risk environments which someone intiated a Hand over request…

2

Risk

Pending states blocked workflows and delayed actions.

3

Shift

This eliminated handover as a failure point in a safety-critical system.

4

Final

Clear ownership + simplified flow while maintaining safety.

Admin → System Governance

Ensures system-wide control, visibility, and compliance.

The admin system was structured across 4 core areas:

• Monitoring → real-time visibility across machines and locations
• Configuration → roles, permissions, and system rules
• Audit & Logs → traceability of actions and responsibility
• Data & Reporting → operational insights and system usage

System Monitoring — Real-Time Machine Status

Provides a live overview of machine states, responsibility, and operational status across locations.

Operations Dashboard — Activity & Performance Trends

Surfaces usage patterns, anomalies, and system activity to support operational decision-making.

Audit / Timeline

Tracks all state changes and responsibility transitions for full traceability and compliance.

System Configuration — Machine Types & States

Defines operational states and rules that govern how machines behave across the system.

Device Management — Tablet Configuration

Manages connected devices and ensures consistent setup across clinical environments.

Impact

Operational impact

Operational impact

• Removed dependency on handovers → reduced risk of stalled workflows
• Made ownership explicit → improved accountability in clinical environments

System impact

System impact

• Unified responsibility and machine state into a single model
• Enabled consistent behaviour across tablet and admin interfaces

Expected impact

Expected impact

Expected to:
• Reduce delays in machine state transitions
• Improve auditability for compliance
• Support safer decision-making in high-risk environments

Next Case Study

Designing a multi-role system for Radiation Safety & Responsibility in Radiotherapy

Designing a multi-role system for Radiation Safety & Responsibility in Radiotherapy