Restoring Healthcare- Smarter Waiting List Management

Whenever delivery in the NHS is discussed, the subject of waiting lists is always high on the agenda. Previous blogs have looked at understanding the data and the human capacity required to reduce waiting lists and restore healthcare. In this blog we explore how digital could improve the management of waiting lists.

The pandemic has seen a massive increase in people on waiting lists across all services.[i] In most healthcare systems there were significant waits before the pandemic. The NHS in England’s 18 weeks standard for referral to treatment has not been met for more than four years and many NHS providers have now switched their focus to 52+ week breaches. The Kings Fund reported that in December 2020 more than 220,000 people had waited more than a year. Behind these figures are individuals in pain or discomfort or with limitations on their lifestyle due to immobility or disability. Further to this, delays in access to diagnosis and treatment are likely to result in poorer health outcomes for many patients.

Hospitals and specialties across the country traditionally manage their own lists and deploy a range of initiatives in an attempt to reduce the backlog with varying results. These include temporary increases in capacity, e.g. waiting list initiatives and outsourcing, and “list management” reviewing people on the list to decrease perceived demand. Many systems appear to manage the list rather than understand the true clinical demand. Waiting lists are complex (mal)adaptive systems. If there are too many people waiting, resulting in prolonged delays to care, then referrals rates from primary care decrease or are “managed” by triage centres. The resulting variation in service provision and management of the waiting lists can exacerbate local health inequalities.

There have been many initiatives over the last 20 years but there is no panacea. How do we measure true demand now and in the future? What about distributing the workload? Or has competition between Trusts for resources and political stubbornness to not move facilities impeded cross-organisational cooperation? How do we make the system more resilient for future challenges, such as new emerging diseases and new treatment modalities, but also more regular challenges, such as winter pressures?

Currently waiting lists are managed locally, by respective departments in the hospital. Most of the time you will be given a time slot to attend with little flexibility. This may be anything from a week to several months in the future. Sometimes, due to issues beyond your control, last minute you will find your appointment cancelled or moved even further down the line. You may even find that the letter for your new appointment gets lost in the post or you receive multiple notifications leading to confusion and increased likelihood of not attending (as we discussed in our blog on screening systems)

Some of the digital solutions that may help reduce waiting lists:

• Predictive Analytics to understand the true demand and its variations – By understanding the known variation, we can make the system more resilient. A health system can plan more effectively if it has accurate predictions of true demand for several years ahead understanding factors such as changes in disease prevalence, demographics, medical interventions.
• Understanding true capacity (Human and Physical) – Could capacity be better linked to demand in the longer term with less need for “initiatives” to reduce waits, as discussed in a previous blog on restoring healthcare. Analytics from a population health view could help reduce health inequalities and support disease prevention and well-being. We have also previously discussed the importance of understanding the data.
• Linking Local Services – Linking local services with joint digital waiting lists could help cope with the huge backlog generated by Covid-19. We know that distributing and sharing the workload is an effective way to get through high demand by increasing flexibility but also by facilitating elective care flow uninterrupted by emergencies. We see this being done everywhere, from small Agile development teams picking up work from the backlog when ready, all the way to large multinational corporations. Digital systems can allow lists to be combined logically from diverse sources without diverting staff away from treating patients.
• Digital Planning – We have seen digital planning of supermarket online orders to optimise a delivery van’s daily capacity by using AI-based predictions of the customer’s needs. One hospital may focus on the continuing Covid-19 and emergency workload, whilst another is kept clean to undertake complex joint replacements and cancer surgery. But digital also allows a more Agile planning that can rapidly respond to changing workload predictions; annual fixed planning should be a thing of the past and more responsive systems developed using digital resource management systems.
• Automation – Staff time can be freed up for direct patient care by automating decision making including prioritisation, suitability, and resource needs. Using machine learning, over time this decision making can become increasingly sophisticated and accurate and need even less human intervention. For example, operating priority could be stratified using Royal College Guidelines via OPCS procedure codes, linked to evidence of clinical severity from the patient record. Patients’ investigations can be predicted and planned to coincide with their one stop clinic appointment. Patients who are deteriorating whilst on the waiting list could automatically be prioritised.
• User Centricity – The NHS is becoming more user centric; a digital waiting list can consider patient preferences on location or time of appointment? Many people have been surprised by the efficiency and simplicity of the digital booking systems for Covid-19 vaccination centres, digital is one factor in the UK’s success in the largest ever mass vaccination programme. Could we not use the same approaches for non-emergency work?

So, what could be the future: What if we imagine a digital waiting list and booking system, that links Trusts across a regional area? Clinicians input what they want a patient to be seen for, and in what time frame. Hospitals dynamic resource management systems know what staff and resources they have available. The patient then logs in from their app, in-puts their preferred location and time, a list of viable options is brought up on screen for them to pick from. A balance between keeping lists down, distributing workload, pathology priority and patient desires could be struck, making the patient journey more user centric whilst maintaining efficiencies. User centred design could also help reduce health inequalities.

Digital waiting lists are not something of the distant future, they are something that can be realised now. Prediction of workload is already possible. Smart lists can be linked across Trusts. The smart waiting lists can use intelligent algorithms to understand demand and to populate patient appointments whilst considering clinical requirements with patient demands. Artificial Intelligence and automation can help free up time to care for patients.

We would love to hear your views on smarter waiting lists. Share them with us on LinkedIn and Twitter.

[i] https://www.kingsfund.org.uk/projects/positions/nhs-waiting-times?gclid=EAIaIQobChMIqPyDm6L78AIVUunmCh3m1wXoEAAYASAAEgK11fD_BwE

Matthew Cooke

Chief Clinical Officer

Matthew Cooke is Chief Clinical Officer at Capgemini. He spent most of his career working in the NHS as an emergency physician and was the National Clinical Director for Urgent and Emergency Care.

Timothy Angelini

Consultant

Timothy Angelini is a Public Sector Consultant at Capgemini. In his previous career he worked the NHS as an emergency physician. He has a keen interest in healthcare remodelling both on a national and global scale.