Steve Barclay recently pledged to harness the full potential of AI technology to tackle some of the biggest challenges facing the NHS, to “improve early diagnosis, reduce waiting times and free up clinician time”.
One area where this technology can provide real tangible benefits is by reducing the number of people who Did Not Attend (DNA) appointments. DNAs cost the NHS more than £1bn a year, and rates have returned to pre-covid levels (8-9%). Why are an estimated 8 million hospital appointments missed every year?
DNAs occur for multiple reasons. Appointment letters can be delayed in the post and arrive too late for the patient to make travel arrangements. Long phone queues can hinder people wishing to rearrange an appointment. People may need clarification on the purpose of an appointment or be vulnerable due to their condition or personal circumstances.
More personalised care is desperately needed to tackle these issues. However, administrative staff manage a substantial volume of appointments, and individualised approaches can be nearly impossible.
A step change in how we tackle DNAs is required. And Artificial Intelligence (AI) and patient engagement technology is part of the solution to unlocking high-volume, personalised care.
Using AI to identify why patients DNA
AI can help trusts predict and prevent missed appointments by analysing data from different domains to build a rich picture of why patients DNA. For example, the DrDoctor AI-driven prediction model draws insights from 35 domains and considers factors such as demographics, appointment times, working hours and travel, and uses this to identify patterns that enable providers to predict who will DNA with high accuracy.
The intelligent risk stratification tool, developed using funding from NHS England’s Accelerated Access Collaborative, uses AI to predict this type of human behaviour. It has shown how people over 65 (who are recipients of free bus passes) are more likely to miss morning appointments because it’s before their free travel starts. Similarly, data shows that working-age adults are far less likely to DNA a morning appointment.
More data is being added every week, to train the prediction model and enhance its accuracy so that administrators have even more insight into which patients need an improved or alternative approach to engagement.
However, this is only half of the story. The NHS workforce also needs time and the right technology to maximise the insight that AI provides.
Patient engagement reduces DNA rates
There’s evidence across the NHS to show how patient engagement technology saves time for NHS staff by automating many tasks associated with patient communication. Letters are digitised and available directly to the patient, reducing the requirement for NHS teams to manage the post and the time patients have to wait for information.
Patients are texted or emailed with appointment times that they can reschedule without the need for manual intervention, saving hours on the phone managing diaries. Text reminders nudge patients to keep to their appointment times. And if someone can’t attend, patient engagement tools make it easy to offer last-minute slots to others so that the slot doesn’t go to waste.
The AI DNA tool works hand in hand with these solutions. For example, the prediction model can identify patients who are 90% likely to miss their appointment. Personalised communications to such groups can be fully automated, which can meet individual preferences whilst saving further time for NHS teams.
Often these cohorts are the most vulnerable and have the highest accessibility needs. Staff now have the capacity to contact them directly and provide a more tailored, meaningful service built to meet their needs.
The same technology can further enhance productivity by safely validating waiting lists and helping remove people from the list altogether. For example, clinically-driven digital Patient Initiated Follow-Ups help release clinical capacity and prioritise care for those most in need by using digital communication channels to confirm which patients still need an appointment.
The future of AI and engaging patients
The impact on provider productivity is evident. For example – customers using the DrDoctor patient engagement platform have been able to reduce DNAs by up to 30%. And we anticipate the DNA AI prediction model to increase this by 18%. Whilst the impact on patient experience is obviously harder to quantify, it’s equally impressive – patients feel more empowered by having their care fit around them and their needs and lifestyle.
Patients today demand more personalised and convenient healthcare services. With the use of AI-powered patient engagement technology, healthcare providers can give people more tailored and productive care in an efficient and scalable way.
By Tom Whicher, CEO, DrDoctor
