TIMELINE
#Healthcare
#UI&UX
#Collabration with Philips
Specialised Product @Umeå Institute of Design
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Group work
A remote health monitoring system that supports tele-health nurses by giving an instant, comprehensive view of each patient’s condition. Beyond transforming fragmented records into clear, interactive visuals, the platform uses AI to anticipate potential future alarms, enabling faster, more confident decisions and improving the overall efficiency of remote care.
Field Visit
Starting with on-site research at NUS Hospital in Umeå, we collected and organized real stories from ICU, PostOp, and Thorax nurses.
It enabled us to distill individual experiences into representative group narratives, deepening our understanding of nurses’ work patterns and providing a crucial foundation for mapping the tele-health nurse workflow.
THe challenges
Through our observations and research, we identified critical gaps in tele-nursing. These became the key challenges guiding our design:
Patient Safety
Inadequate Context
Increased risk of errors
Strain on Tele-health Nurses
Lack of Time-based insight
TImeline
Events → Context
From our research, we found 4 main event types that offer tele-health nurses the essential context for quickly understanding a patient’s situation.
Comments
Enables nurses to record observations and exchange information.
Alarms
Different colors indicate alarm types, while the length of each icon represents its duration.
Medical events
Shows the patient’s medical history, including treatments and diagnoses.
Media/Activity
Captures important moments to give nurses visual context beyond textual data.
Monitoring View for Tele-Nurse
The tele-nurse interface consists of two screens: the left provides an overall monitoring view, while the right offers a detailed view of a single patient. The overall view shows a condensed 4-hour timeline, whereas the detailed screen breaks down the patient’s history more comprehensively, enabling nurses to quickly spot trends and make informed decisions.
General Patient View and Predictions
A compact timeline view consolidates alarms, medical events, and patient activity. In the lower-right corner, an AI-driven prediction panel uses historical data to forecast potential conditions — for example, hypoxia — enabling early intervention. Alarms are also contextualized: when triggered, the system provides AI-generated insights into possible causes (eg.Blood Sample caused the red alarm).
Patient Overall View
Within this page, tele-nurses see a 4-hour view that compiles events alongside patient data and provides a smart hourly summary of what happened, with a general patient information tab on the right for quick access to key details.
The Related Events
Since events are interconnected, tele-nurses get a complete picture of the patient’s condition. Clicking a prediction surfaces the most recent related events — for example, patient movement — along with associated red and blue alarms, while the right tab displays event details.
Zooming In&Out of the Timeline
Jumping to Another Event
Communication Feedback Loop
When an event occurs, both the tele-nurse and bedside nurse document the treatment provided, ensuring a shared understanding of the patient's history and reducing the risk of communication errors.
Behind the scene
