AI in the NHS: Predicting DNAs and Transforming Outpatient Care

30th September 2025

by John Clarke

Did Not Attend (DNA) rates have long been a thorn in the side of the NHS and healthcare providers worldwide. Missed appointments waste clinical resources, extend waiting lists and negatively impact patient outcomes. Traditional reminder systems, such as SMS alerts sent at fixed intervals, have delivered only modest improvements. But, what if we could predict which patients are most likely to miss their appointments and intervene intelligently?

But, what if we could predict which patients are most likely to miss their appointments and intervene intelligently?

That’s exactly what a recent pilot study explored, using DNA Artificial Intelligence (DNA AI) integrated into the Netcall Patient Hub. The results are not just promising, they signal a new era for AI-driven healthcare engagement.

The pilot: AI meets patient communication

The study, conducted with The Rotherham NHS Foundation Trust, tested whether AI-enabled risk stratification and targeted messaging could reduce DNA rates in outpatient clinics.

Here’s how it worked:

  1. AI risk prediction: Using historic attendance data, the DNA AI model predicted the likelihood of a patient missing their appointment. Factors included prior attendance, demographics, service type and appointment timing.
  2. Risk-based messaging: Patients in the high and very high DNA risk bands received an extra SMS reminder one day before their appointment, in addition to the standard 7-day and 4-day reminders.
  3. Controlled trial: The design compared intervention and control groups across April (baseline) and July (intervention), accounting for seasonal and external factors.

The results: A game-changer for high-risk patients

Both groups saw some reduction in DNA rates, but the intervention group’s very high-risk patients experienced a dramatic improvement – from 48% DNA in April to just 16% in July. This is a two-thirds reduction in missed appointments for the most challenging cohort.

Key takeaways:

  1. Contact centre optimisation (Liberty Converse): AI-powered triage and conversational bots to reduce call volumes and improve first-contact resolution.
  2. Proactive patient engagement: Predictive analytics to identify patients at risk of non-compliance, deterioration or disengagement.
  3. Workflow automation (RPA + low-code): Automating repetitive admin tasks, freeing staff for patient-facing care.
  4. Intelligent document processing: Using AI to extract and process clinical and administrative data, reducing delays and errors.
  5. Population health insights: Leveraging AI to identify trends, predict demand and support preventative care strategies.

The direction of travel: From reactive to predictive healthcare

The DNA AI pilot shows what’s possible when predictive intelligence meets personalised communication. Imagine scaling this approach across every patient interaction: Appointments, medication adherence, follow-up care – powered by a single, integrated platform.

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“The future of healthcare engagement is predictive, personalised and proactive and AI is the engine driving that transformation.”

John Clarke

Head of Client Solutions – Health, Netcall

A call to action for NHS Trusts

If your trust is looking to reduce DNAs, improve patient experience and optimise resources, now is the time to act.

About the author

John Clark

Head of Client Solutions – Health

John has a wealth of experience from the health sector, having worked in the industry for over two decades. He's passionate about helping drive change in the NHS and streamlining it for both NHS professionals and patients. John aims to to make a positive difference to society when it comes to the delivery of healthcare across our communities.

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AI in the NHS

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