Yee Ting McCloy

Product Designer & Illustrator

I’m passionate about transforming data into elegant and accessible user interfaces and following the entire process from user research, flows, and user personas - through to wireframes, pixel-perfect high fidelity prototypes and QA/front end development.

The Challenge

Hospitals are doing their best to manually predict approximate waiting times for patients, using current and historical A&E data but this can be inaccurate and often patients are left with long periods without visibility of their patient journey. In an NHS survey of 31,168 A&E patients, 59% of respondents said they were not told how long they would wait before being examined and 35% of patients either couldn’t find somewhere to get a suitable meal or weren’t even aware they were allowed to eat or drink. It therefore comes as no surprise that patients are left feeling extremely frustrated and distressed at a time when they’re already in a very vulnerable position.

My Role

The Solution

Reducing A&E waiting times is the ultimate goal, but while we strive to get there, we need to focus on creating a better patient experience and one way to do this is to provide transparency of the patient journey.

Using a data centric platform would enable Trusts to more accurately predict waiting times and display real time data on screens in the A&E waiting area as well as a patient facing application to transform the patient and user experience.

So, how would the solution work?

Let’s say a patient has come into A&E with an injured leg after playing football. Upon arrival, they are seen by the A&E administrator and diagnosed with a suspected leg fracture. They are then assigned a patient number, password and, given a QR code to download the NHS app. They’re also told to keep their eye on the screens in reception for updates. The patient downloads the app and logs in with their patient number. They are presented with a timeline displaying their unique patient journey. The app is already showing the first step they completed when they saw the A&E administrator at 09:36 and they now have an estimated 32 minute wait before their assessment with the Triage Nurse. When the patient is ready to be discharged, due to nature of their injury, the app will prompt them to either call a friend to pick them up, or to book a taxi.

In this patient’s case, they are facing a number of lengthy waiting periods, giving them the opportunity to visit a café for refreshments. The application can be designed to notify and encourage the patient to visit the café to give them an opportunity to get something to eat or drink. It is also designed to encourage patients to move to a more relaxing and comfortable waiting area, while helping to prevent overcrowding in the hospital’s main A&E waiting area.