AI_Kiosks_Ending_The_Dangerous_Waiting_Room: Turning the story of a patient or child into a safer, structured care plan
For more than four decades, I have watched one of the most important parts of healthcare unfold before any test is ordered and before any treatment begins.
Someone tells a story.
A parent describes what has changed in their child. A teacher explains what she has observed in the classroom. A nurse notices something different from yesterday.
A psychologist listens to behaviour that may have developed over months or years. A doctor brings all these pieces together to decide what matters. The quality of the decision depends heavily on the quality of that story.
This is particularly important when caring for children with physical disabilities, learning difficulties, developmental problems, behavioural changes or mental-health concerns. Parents may notice one part of the problem, teachers another, psychologists another and doctors yet another.
The challenge isn't that people don't care. The challenge is that the information is often fragmented. That is the problem I'm trying to solve with Dr Maya AI.
From a symptom checker to a listening assistant
Dr Maya is not being developed simply as another symptom checker. The new six-colour system is designed so Maya can act as an assistant to doctors, nurses, parents, carers, and teachers.
The system first listens to the story.
It identifies the significant symptoms, signs, behaviours and concerns.
It looks for a pattern across several findings rather than deciding from a single symptom. The current instruction specifically asks Maya to reason through patterns of three or four findings and to consider the main problem, duration, speed of change, age, associated symptoms, vulnerability and what the person is most worried about.
That is important because real clinical reasoning rarely begins with one isolated symptom.
It begins with the pattern.
Why six colours?
I expanded the Maya framework to six colours because the problems children and families face are not purely medical.
The revised system recognises six different categories.
Blue represents infection requiring isolation precautions.
Red represents serious or emergency medical concerns.
Orange represents developmental or behavioural concerns.
Black is the “doesn't fit” category — an unusual, new or uncertain pattern that needs further medical evaluation rather than being forced into an inappropriate diagnosis.
Green represents moderate concerns.
Yellow represents mild problems.
This creates a much broader framework than conventional medical triage.
A child may not need a hospital. The child may need a psychologist. Another may need a psychiatrist. Another may need a paediatrician. Another may need a nurse.
Another may primarily need support from the class teacher. And another may simply need observation and appropriate home care. The purpose is therefore not to send everyone to a doctor. It is to help identify the right person to help with the right problem.
The lesson I learned during validation
While validating Dr Maya at JDC Sparsha Academy, I observed consultations in which parents described their child's history while teachers and psychologists contributed their own observations.
Dr Maya AI listened to the same story. It organised the problems. It identified relevant patterns. It compared physical, behavioural and psychological concerns. And it proposed an appropriate next level of care.
That experience reinforced an important principle.