Ideas — good ones — can strike in unexpected places.

For Associate Professor Ng Lay Guat, her eureka moment happened when she was in a public toilet! “I could hear the person in the next cubicle. As a urologist, I can tell when there’s perfect or slow flow of urine. That’s when I realised that our brain has the ability to analyse it, so why not get an app to do the job? I guess it turned out to be a useful occupational hazard!” said Assoc Prof Ng, Senior Consultant, Department of Urology, Singapore General Hospital (SGH).

She went on to develop a mobile app that can detect abnormal urine flow. When implemented, the app will potentially shorten clinic waiting times as patients can then do certain tests at home before arriving at the clinic. Now in the testing phase, the app is likely to be launched within the year by the SGH urology team led by Assoc Prof Ng.

Patients being treated for urological conditions routinely undergo a standard test called uroflowmetry, where they urinate into an electronic machine. The data gathered help doctors determine the effectiveness of the treatment and whether modifications are needed. However, to be accurate, the test needs to be done when the patient’s bladder is full; otherwise, the result may be inconclusive.

“The clinic can be a stressful environment for the patient. Having other patients behind them in the queue waiting for the same test can cause some anxiety, so they quickly do the test even when the

bladder is not completely full,” said Dr Edwin Jonathan Aslim, Consultant, Department of Urology, SGH. Inaccurate test results lead  to patients having to re-take the test, adding to their waiting time as they wait one to two hours for the bladder to fill up again. They may even have to return on another day, added Dr Aslim, a member of the team.

With the app, patients can repeat the test stress-free at home as often as they want, giving doctors a clearer picture of their condition. Using the app will also free the nurses to focus on patients needing greater attention. With the standard method, nurses need to bring the patient to the machine, clear the urine and replace the container when the test is done.

The team is developing the app with the Singapore University of Technology and Design to capture data such as the speed and volume of urine passed out. It can also determine patterns, such as whether urine flow is intermittent or continuous.

A 2017–2019 SGH study helmed by Assoc Prof Ng collected data that was then used to develop a deep-learning algorithm, which processes data collected through the app. Besides measuring urine flow, the app has other useful functions like creating a voiding diary. “We want to make sure the interface is helpful and user-friendly too; otherwise, it won’t be widely used,” said Dr Aslim.

When launched, the app can provide doctors with very important data. “For instance, slow flow can be an indication of obstruction in male patients with enlarged prostrate,” said Assoc Prof Ng. In women with overactive bladder, the app can measure urine volumes for use in maintaining a voiding diary. Patients now manually measure and record the volume each time they go to the toilet.

Assoc Prof Ng hopes the app will eventually be used in the primary healthcare setting, where patients with stable conditions can be followed up. The app will give the polyclinic doctor or general practitioner access to actual parameters instead of depending on patient’s description, which can be subjective.

Aside from these, the app also makes for a good screening tool for the general public. “If patients detect anything abnormal on their apps, they can consult a doctor. With further tests, we can then make a proper diagnosis,” said Assoc Prof Ng.