Hospital waiting lists are a worldwide problem, with millions of patients experiencing delays in receiving medical care. Extended wait times can lead to worsening health conditions, increased patient anxiety, and overall dissatisfaction with the healthcare system.
In the UK, approximately eight million people are currently waiting for treatment on the NHS. This backlog is not only frustrating for patients but also poses significant health risks, as conditions can deteriorate while waiting for care. The economic implications are equally concerning; ill health often results in reduced productivity and increased absenteeism from work.
At Deep Medical we are committed to reducing NHS hospital waiting lists by using AI to streamline processes and increase patient access to the care that they need.
Here are seven ways in which we can reduce the NHS waiting list.
1. Reducing no-shows
No-shows are a huge headache for healthcare providers, with millions of missed appointments annually.
At Deep Medical, we’re using AI to predict no-shows by analysing patterns in patient behaviour and history, and we can do this without accessing individual patient medical records.
Our AI-driven system, DM Connects, can predict which patients are in danger of missing their appointments. The result? The hospital can reach out to the patient, and reschedule their appointment at a time that’s more convenient for them.
And if the patient cannot be reached, the system automatically moves another patient from the hospital waiting list into the vacant slot.
Our pilot programs across huge NHS Trusts have shown that this approach can reduce patient no-shows and increase the number of patients seen, thereby reducing hospital waiting lists.
2. Smoothing out the working week in NHS clinics
There are six million outpatients on the NHS waiting list and eight million missed appointments each year. Each missed appointment represents a doctor’s time wasted and a patient’s health put on hold.
By increasing clinic efficiency, we believe we can boost clinical capacity and reduce the NHS waiting list.
Missed appointments present a huge challenge for clinics as they’re not consistent week on week. One week, no-shows might be 4%, the next week, 11%.
This inconsistency forces clinical staff to either sit around if there’s a no-show (or use the time to catch up on admin) or work late. Not ideal, or a good use of their time.
But it’s not just about one patient missing one appointment; it’s about the efficiency of entire clinics and the well-being of the amazing staff and clinicians who work there.
Using AI, we can address the waiting list issue. Our DM Schedules software uses AI to dynamically manage clinic capacity, aligning the clinical workforce perfectly with patient demand.
The result? Clinics can optimise their schedules and improve their efficiency, resulting in more patients being seen and shorter waiting lists.
3. Building stronger patient communication
Communication issues can often lead to missed appointments. For instance, a patient with visual impairment may struggle to read a letter, while a patient whose first language is not English might have difficulty understanding the instructions.
We believe that effective communication means reaching patients in a personalised way on a platform that is suitable and convenient for them.
Our DM Connects system uses AI to send personalised communications through the preferred channels of each patient, whether it be text message, email, or phone call.
This system also schedules reminders to ensure patients attend, cancel, or reschedule appointments ahead of time, improving engagement and attendance rates.
As a result, more patients receive timely care, reducing the waiting list.
4. Building stronger patient relationships
NHS volunteers are the lifeblood of the health service; the 100,000 volunteers currently working in the NHS help around 8 million patients per year, and their local knowledge means they’re well-placed to understand the barriers patients face in attending their clinical appointments.
We’ve been working with volunteers across two NHS Trusts recently, training them to use our DM Schedules software. These volunteers have been working alongside hospital booking teams to engage with patients at risk of missing appointments.
This personalised approach helps build stronger relationships with patients. The volunteers understand the challenges that patients can face in making it to a hospital appointment. Challenges such as transport issues, needing support when they arrive at the hospital, or an appointment date that works better with their work or caring responsibilities.
We believe that by building stronger patient relationships, we can increase the likelihood of patients attending their appointments, and so far results have been really encouraging.
Improved attendance rates mean better health outcomes for patients and greater clinic efficiency, ultimately reducing waiting lists.
5. Learning lessons from Covid
The Covid pandemic created unprecedented challenges for the NHS, leading to a significant increase in the number of cancelled or rescheduled appointments. But it also prompted some NHS Trusts to think how they might work differently to reduce the enormous backlog.
From so-called ‘superclinics’ operating in the evenings and weekends to streamlined workflows, a number of Trusts have adopted new practices to tackle the waiting list. In many cases, these measures have substantially reduced waiting times and have been successfully integrated into daily operations.
6. Addressing frailty
Sometimes tech isn’t the answer, particularly for older patients.
Older patients can often have complex health and medical needs that require a more tailored and ‘people-centred’ approach. And while technology can enhance clinical efficiency, this demographic often need more personalised care.
Our DM Pathways software uses AI to identify frail patient groups where poor compliance is a clinical concern. By highlighting these patients to clinical teams, we ensure they receive the necessary attention and care.
This approach leads to more efficient management of older patients’ care, improving their clinical experience, increasing overall capacity and reducing waiting lists.
7. Improving public health
At Deep Medical, our overall mission is to reduce health inequality by helping patients access the care they need. We believe that by reducing waiting lists, we can help to improve public health so that everyone, no matter their background or circumstances, is left behind by the healthcare system.
Ultimately we want to abolish the NHS backlog, leading to more efficiently run clinics, happier clinicians, treating a healthier population.
By using AI to contact and connect with patients, we can focus on improving public health, to ensure that all patients receive timely and high-quality care.
Conclusion
At Deep Medical, our mission is to reduce NHS waiting lists, using AI to streamline processes and enhance patient access to necessary care.
Our approach includes reducing no-shows, optimising clinic schedules, improving patient communication, and building stronger patient relationships. By doing so we’ll be creating a more efficient healthcare system that improves overall patient outcomes.
We want to ensure timely and high-quality care for all patients, paving the way for a healthier and more equitable future.
