Here is an article I wrote about using AI to help manage our NHS orthodontic waiting lists. By screening everyone, we were able to see the right patients faster, increase capacity and reduce waiting times.
Just recently I found myself asking a question that had been bothering me for several years.
As we approached the final quarter of the NHS year, the pressure in the practice would begin to build. Quarter four became a race against the clock as we tried to deliver the final part of our Orthodontic NHS contract. Every January and February seemed to follow the same pattern. The team would come back after Christmas knowing we had a push on to deliver the contract. They always rose to the challenge and worked incredibly hard, but it never sat comfortably with me. It felt as though we were asking people to work harder to compensate for something in the system that wasn't working as well as it could.
What I couldn't understand was that demand clearly wasn't the issue. We had around 1,400 patients (2 years) on our waiting list, referrals were continuing to arrive and our orthodontists were fully booked. So why were we constantly chasing the contract rather than comfortably delivering it?
As a business manager, when something doesn't make sense, I tend to start with the numbers. They rarely tell you the whole story, but they nearly always tell you where to start looking.
I began with the assessments each clinician was carrying out every week, and comparing them with the number of NHS starts they were generating. The orthodontists were seeing between 21 and 23 assessment patients each week but only around nine or ten were actually starting treatment. To comfortably deliver our contract we needed that figure to be closer to twelve. That might not sound like a huge difference, but over the course of a year it becomes significant. By the time we reached the final quarter, we had created a gap that could only be closed by asking everyone to work even harder.
My initial findings were that many patients simply weren't ready.
Some still had deciduous teeth and needed a little more time before treatment could begin. Some had oral hygiene that wasn't good enough for orthodontic treatment. Some were clearly more appropriate for secondary care. Others were unlikely to qualify for NHS treatment under IOTN, whilst a small number simply hadn't appreciated what orthodontic treatment involved until they were sitting in the chair discussing extractions and two years in fixed appliances.
The problem was that we were using specialist assessment appointments to discover information that, in many cases, we could have uncovered beforehand.
Around this time I was talking with Lisa from Dental Monitoring about Engage, previously known as SmileMate. It had originally been developed as a lead generation tool, particularly during the COVID period, but as we talked, I began to wonder whether we could use it for something completely different.
Rather than generating leads, could it help us understand our NHS waiting list before patients attended for assessment?
We decided to give it a try.
Patients were sent a link asking them to upload a series of photographs and complete a short questionnaire. The questions weren't complicated. Did they understand why they had been referred? Would they be prepared to have extractions if required? Would they like to have braces? The purpose wasn't to make clinical decisions remotely. It was to encourage families to start thinking about orthodontic treatment before they came through the practice door.
The photographs were then analysed by Dental Monitoring's AI, highlighting things such as retained deciduous teeth, obvious oral hygiene concerns and other features that might influence the patient's pathway. One of our orthodontic therapists reviewed the AI report alongside the photographs and questionnaire before deciding what should happen next.
This was where the process really began to change.
Patients who appeared ready for assessment were booked directly with the orthodontist.
Patients with poor oral hygiene received advice, were directed to our hygienist where appropriate and were asked to submit another set of photographs a few weeks later.
Patients who looked more appropriate for secondary care were discussed with the orthodontist before being directed down the hospital pathway.
Patients who appeared unlikely to qualify for NHS treatment were contacted by our treatment coordinator so that they understood all of their options before attending the practice.
Instead of every patient following exactly the same route, they were directed towards the pathway that best matched their circumstances.
What surprised me was just how much difference it made. The orthodontists spent less time identifying issues that could have been addressed weeks earlier and more time making clinical decisions. Assessment appointments became more productive because patients were arriving at the right point in their journey rather than simply when they reached the top of the waiting list.
When we analysed the figures, we estimated that the process had created the equivalent of around 364 additional clinical appointment opportunities each year.
We hadn't recruited another orthodontist, built another surgery or increased our opening hours. We had simply made much better use of the clinical time we already had.
The additional capacity brought other benefits that we hadn't anticipated. We were able to work through patients requiring secondary care much more efficiently. Our hygienists saw around 30% more patients because oral hygiene support became an active part of the pathway rather than something identified during assessment. Patients who didn't qualify for NHS treatment were no longer surprised by that conversation, and our conversion into private treatment increased significantly because families had already begun to understand their options before attending the practice.
Most importantly, our NHS assessment conversion improved from around 40% to approximately 70%. That single improvement fundamentally changed our ability to deliver the NHS contract without the annual scramble that had become accepted as normal.
Looking back, we didn't create more capacity. We simply stopped wasting the capacity we already had. Instead of asking, "How can we see more patients?", we started asking, "How can we make every assessment count?"
The technology gave us information earlier. DM Engage highlighted patterns we would otherwise have had to find manually, but technology didn't redesign our patient journey. Our team did.
The orthodontists, orthodontic therapists, treatment coordinator, hygienists and reception team all had clearly defined roles. AI simply enabled each of them to make better decisions with better information.
There is a great deal of discussion about AI in dentistry at the moment, much of it centred on what it might do in the future. Our experience was much more straightforward. We used it to solve a practical operational challenge, improve NHS contract delivery and create additional capacity without increasing clinical resource.
For me, that's where the real value of AI lies - not in replacing people, but in helping good teams work even better.
If this article has sparked a few ideas, you may find the accompanying webinar useful. In the session, I walk through the complete process we developed at Sussex Orthodontics, including the patient pathways, AI-supported screening, team workflows and the practical lessons we learned during implementation.
You can watch the webinar here: Your waiting list isn't the problem. Your triage is.
Book a conversation and we can review your current pathway, waiting list pressures and triage model.