Commando
Design Sprint
1 week
Eliminating Decision Fatigue in ER staff using AI
Emergency medical staff must maintain high cognitive readiness to manage rapid-fire, high-stakes decisions. To mitigate the risks of decision fatigue and mismanagement, Commando centralizes real-time data into a single hub. This streamlines communication and ensures team-wide clarity without overextending personnel.
3+
Target users contacted
2
Peer review sessions
My roles
UX Designer
Tools
Base44 (AI prototyping), Lovable (AI ideation), Figma
Team
Solo project
Duration
1 week
Gallery
गॅलेरी
Context
परिस्थिती
My family has doctors - a LOT of them. Many of them are senior professionals, and even more are joining in as doctors.
Doctors of the family and me!
From anecdotal experience (and complains from my cousins), I found that ER shifts were the most difficult. Despite the vast improvements in ER management technology, many staff members still found it exhausting. Hence, I asked the question:
How can I improve the ER experience for staff members?
With this goal in mind, I proceeded with learning more about this space.
Interviews with:
2 Doctors
1 Developer
Insights:
Interruptions
Approximately every 10 minutes
Fast-paced
Impactful decisions made in minutes
Alert Fatigue
From excess notification
Current System:
Communication
Multiple ways of getting a message
Synchronous
Calls & pagers preferred
Random pairing
Teams made minutes after assignment
It was clear that staff members had many ways to communicate synchronously, but organizing this exchange of information was difficult. I created a HMW based on this information:
How might we help manage information for ER staff?
Process
प्रक्रिया
I began sketching interactions, from which I was able to refine the prototype and validate my ideas.
Initial conceptualization
Quick Prototypes
Using generative AI, I was able to make quick, responsive prototypes. This expedited the concept validation process, allowing me to take more data-driven decisions in this 1 week sprint.
First round prototypes for initial testing
After some feedback sessions from my peers, I was able to pick a direction which had high impact and feasible to develop in the timeline.
Product
प्रॉडक्ट
By using AI prototyping tools, I was able to develop a fully functioning web application. I updated the quick prototypes to be more high fidelity, and introduced additional features.
Prototyping an entire application in <3 days
Real-time updates
Tasks provide relevant information such as urgency, members required, etc. which previously needed to be communicated manually.
Assigning Staff Members
Staff members can be easily assigned different tasks by drag and drop, without manually sending a request or a message.
Auto Assign
Lower priority tasks can have staff members automatically assigned.
Challenges
I learnt pretty quickly that AI can create really high fidelity interactions, but cannot replicate my designs if I give them as inputs. It could get the general idea, but not the final product.
AI wasn't able to replicate the designs I made in Figma
I had to also change my inputs, going from mainly hand-made designs with few prompts for refinement to complete prompt-based designing with a few minor hand-made changes.
Changing my approach for designing
What I learned
Starting is key
I had a hard time knowing what I needed to do before starting the project; I had never done a solo UX sprint before, and naturally I was afraid. It wasn't until I gave myself a strict timeline and planned out my week that I overcame the inertia and gained momentum going into the sprint.
Don't be afraid to experiment
Due to the nature of the sprint, I found that using generative AI iterations to create this prototype was an excellent way to build something that people could actually use, without overwhelming myself. There was a learning curve going into this; I was more used to moving pixels by hand, and not so much saying what I wanted. As I looked up more tutorials and ways I can improve, I found myself enjoying the process of making something that actually existed.
Thank you for reading!
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