A decade of Staffing shortages, low bed capacity and a devastating 2-year pandemic has culminated in an unprecedented backlog of elective procedures for the NHS with over 7 million patients currently waiting for care in England1.
As a response to these growing waitlists, the NHS conceived the national high-volume low-complexity (HVLC) programme during the COVID-19 pandemic. This programme has worked to standardise pathways, introduce surgical hubs, and improve theatre productivity to increase the throughput of trusts performing routine procedures. It has long been suspected however, that routine procedures in the NHS are not as low complexity as they were before the pandemic2. This is in part due to increasing prevalence of long-term illnesses3, an ageing population4, and the degradation of patient health whilst waiting for surgery2.
As part of our work supporting the GIRFT HVLC programme, we have worked with surgeons to identify patient characteristics that have statistical relationships with the cost of high-volume orthopaedic surgery procedures. These include clinical diagnoses, such as cancer or diabetes in patient records, procedural features, such as the emergency admissions prior to surgery, or patient demographics, such as age and deprivation. Using Machine Learning approaches, we can quantify the impact of these features and develop an indicator of clinical complexity in routine procedures. Our work brings light on the poorly understood impact of increasing patient complexity and is the first step towards mitigating and tackling the increased burden being felt by surgical specialties in England.
To quantify patient complexity, 2 key data sources have been used.
Hospital Episode Statistics (HES), a detailed dataset containing clinical, demographic, and patient information.
Patient Level Information and Costing Systems (PLICS), a dataset relaying the cost of hospital admissions in England.
By linking these two sources, we have been able to create statistical models that uncover the relationship between clinically relevant patient features and the cost of a procedure. Specifically, we have worked with Orthopaedic surgeons to select 22 drivers of operation cost which are shown in Figure 1.
HES/PLICS data from 2018-19 was used to extract these features and train procedure specific linear regression models that estimate procedure cost. Using these models, we can track the estimated cost that is driven by the clinical characteristics of the patient over time which is a pertinent indicator of patient complexity.
The expected costs have been calculated for 3 major HVLC orthopaedic procedures in Figure 2. They clearly show that since the COVID pandemic, patients have been more complex and resource intensive than ever before. Analysis of patients has revealed this increase is primarily driven by increased frailty, as there is a 30% increase in patients with a severe frailty score, as well as a 10% increase in the average number of significant ICD-10 codes. Worryingly, this increase shows no sign of reversing as of March 2023, suggesting that this trend is potentially here to stay.
This work reveals several far-reaching implications for the NHS, most notably that routine procedures are likely to drain resources more rapidly than ever before. Unless hospitals are paid accurately to reflect these changes, there will be a reduction on how much can be spent on staffing and other resources which further damages patient care. We have compiled a set of key recommendations that aim to mitigate the knock-on effects of complexity increase.
Increased cost and resourcing requirements should be reflected when creating activity plans. This will affect trust, care system and specialty managers with limited budget.
Tariffs should be regularly updated to reflect the ever-changing patient case mix that is seen by hospitals. The tariffs should also be sensitive to demographic features of patients, such as age and deprivation, as we have found that these are important drivers of surgery cost.
Programmes should focus on increasing the general health of patients before elective admission. We have shown that the increased expected costs of hip replacements alone amount to over £13 million pounds per year for the NHS. If programmes, such as the PREP-WELL project by the health foundation5, can demonstrate that they are able to reduce clinical complexity, there is large potential for savings.
National programmes that track surgical outcomes, such as Model Hospital and the National Consultant Information Programme, should adjust performance metrics to account for changing patient case mixes. This will enable increased buy in from clinicians who have been most directly affected by increased complexity.
Engineering and insights to support elective recovery and hub-based working with GIRFT and NHSE
One of the ways in which the NHS is trying to reduce the list of patients waiting for surgery is by enabling increased theatre throughput. A method of achieving this is bundling high-volume, low-complexity surgeries together and thus operating on these more efficiently. To understand the impact of this nationally as well as monitor implementation over time, GIRFT and the NHS more generally needed to collect theatre data on a national scale and refresh it regularly.
Several teams in NHSE and GIRFT were stood up to work on this. Edge Health was asked to assist this work by supporting part of the data collection, the engineering once the data was available, help assess the data quality and analyse the data to provide insights into the effects of theatre efficiency, both generally and at hub-based level.
Data Collection: We ensured consistent data collection of all theatre systems
We supported the data collection by working with key stakeholders to identify what data was available and required to answer the question at hand. We then designed a data request for a one-off collection and collaborated with the national data collection teams to obtain data from their regular collection.
Engineering: We designed a system that could be robust, interpretable and updated regularly
Theatre data across all trusts, updated every two weeks requires significant streamlined plumbing under the hood to ensure accuracy, replicability and ability to use the data across teams. We therefore engineered a solution that fit into a Microsoft Azure based data platform, utilising Storage Accounts for reference and input files, Azure Data Factory to orchestrate and carry out the processing and Azure Synapse as a data warehouse from which the data could be consumed from.
Data quality: we put a process in place that flags and automatically improves data quality
As part of the process, we created a virtuous loop of data quality improvement. For every cycle update (i.e., trusts submitting data, engineering pipeline refreshing it and insight being generated), we produce automatic flags and updates that enable feedback to trusts about data quality issues.
Insights: We generated insights that are used around the country
Using the cleaned, processed data, we worked with clinical leads, theatre experts and Trusts to develop analysis to demonstrate opportunity across all theatres in the country. Particularly, we were interested to model what would happen if Trusts were able to schedule and operate their high-volume, low-complexity cases in a routine way, thus hitting the activity levels suggested by early hubs and clinicians trailing the concept.
The analysis suggested that Trusts could significantly increase throughput and reduce the waiting list quickly. That work has since fed into new funding models for hubs and advanced roll-out of the measures across the country. Our robust system ensures the NHS is able to update and track improvements over time across 110 providers and 39 systems as it moves forward towards elective recovery.
Elective Recovery: understanding targets and finding opportunities to increase activity
The first quarter of 2022 saw the launch of NHSE’s elective recovery plan, setting out a trajectory to carry out 30% more elective activity by 2024/25 than before the pandemic. The first goalpost was set at achieving a 10% increase in completed pathways during 2022/23, with additional funding available for providers delivering 4% more valued-based activity compared to 2019/20. However, as of October 2022 the targets were unmet by the majority of Trusts.
A specialist provider in London reached out to Edge Health to gain a deeper understanding of targets in practical terms and scope potential solutions.
Deep insights to model solutions
Our strategy had two tangible targets:
Understand the issue deeply through multiple on-the-ground interviews, capturing staff’s key concerns, and evaluate current and past activity to reflect NHSE’s value focus.
Analyse past and present valued activity to produce a user-friendly model to assess how much activity by point of care and team would be required to meet NHSE’s targets.
Clarifying the meaning of valued activity and the 104% vs 110% targets was central to the success of our work.
Essentially, a 104% valued activity target was set to avoid an achievement of the 110% target exclusively through reducing outpatient follow-ups and completing more referrals in primary care. Tariffs are applied to obtain valued activity, so that inpatient elective pathways are far more valuable than day cases and outpatients. In our client’s case, despite excelling at completing outpatient pathways, they were unable to meet the targets due to the value-weighting placing more importance on inpatient activity.
The technical and clinical expertise of our team was key to uncover the key reasons behind our client’s difficulty in meeting elective recovery targets. Particularly, we identified a significant increase in patient complexity leading to prolonged case duration in theatre, contributing to a reduced throughput.
Conversations with staff highlighted concerns over staff changeover with a shift towards less senior team members, as well as low morale following COVID-19 and NHS pension concerns affecting the appetite for overtime work. Our analysis also revealed significant losses in theatre staffing, mirrored nationwide, since 2019/20.
We proposed actionable and achievable recommendations spanning various opportunity areas and evidenced their resulting effect on activity recovery, to support prioritisation and a focus on the solution, not just the problem.
A local team empowered to tackle elective recovery
Our client gained clarity on elective recovery target requirements and the reasons contributing to the activity gap. This empowered the local team to look for solutions such as team expansion where needed and tackle elective activity through addressing theatre scheduling, fallow activity and utilisation.
Driving data quality improvements to support elective recovery
As the NHS continues its progression towards the era of data-driven healthcare provision, the importance of high-quality data continues to grow. Commissioners and providers, now more than ever, rely on data to signal under- and overprovision of services, so that limited resources can be reallocated where they are most needed, and more patients can receive the care they need, quicker.
With data lying at the heart of this process, it is crucial to maintain and improve its quality. This can present a challenge to operational and business intelligence teams that are already strained under the ever-growing administrative burden of numerous internal and national data collections and reporting.
Edge Health worked with a large NHS trust, supporting them with improving their waiting list data quality. The details of this work are presented below. Off the back of this work, all records on the inpatient and outpatient waiting lists were validated by the operational teams, with more than 370 erroneous records corrected within the first 2 months of use. Internal processes were also put in place to minimise the chances of further errors occurring and to correct those that do fall through the cracks.
The importance of high-quality accurate data in the NHS is growing
Data forms the backbone of healthcare decision making infrastructure. “How many patients are waiting?”, and “What are they waiting for?” are the key questions that determine the focus of short- and long-term service planning efforts. In the light of exploding waiting lists, answering these questions is of paramount importance – knowing the answers allows Trusts to put their efforts into the aspects of delivery that would make the biggest difference to patient outcomes.
Waiting list data is prone to error, resulting in delayed treatment
In order to answer these questions, one would need to dive into what is known as the PTL. PTL stands for Patient Tracking List which is exactly what it says on the tin – a list of patients waiting for elective care. In the past to find an answer to this question, one would physically go through stacks of paper files stored in a hospital. Unsurprisingly, this was a very error-prone process, with patient files falling through the cracks (potentially quite literally). Luckily, now that the NHS is moving digital, the days of sifting through the physical paper files are over (fingers crossed…). However, digital data can still be (and often is) full of errors.
We have worked with many datasets across all care settings and have seldom found a dataset without errors. It is easy to get desensitised to the concept of data quality issues, but we should always remember that in the context of healthcare, there will be a personal story behind every number. Data quality issues can lead to patients going missing and not being called in for their procedure, valuable resources mis-allocated or misinformed staffing decisions made. Knowing the cost of inaccurate data, a large Trust decided to partner with Edge Health to tackle the data quality issues in their PTL.
Edge partnered with a large Trust to support them with improving their waiting list data
We worked closely with the Trust’s internal team to identify and fix their data quality issues. We did this as follows:
1. Identify criteria for erroneous records
Firstly, we held a series of workshops with the operational leads to establish the criteria for erroneous records and to come up with a way of identifying those through manual inspection of the records held in the database. For example, we discovered that lots of patients with pre-op activities were disappearing from the waiting list before completing their treatment – pre-op activities often closed the referral to treatment pathway. As a result, patient records were falling through the digital cracks of the PTL.
2. Fix existing errors
Once the approach was signed off and we knew what to look out for, we extracted erroneous records from the internal databases and provided these to the operational leads, who were able to take action to correct them. For example, when a patient was lost and not invited for treatment on time, the team were able to reach out to them and call them in. Many errors (such as typos) were fixed simply by correcting the data stored in the database.
3. Establish source of errors and review policies
We then set off to identify the source of the errors so that a process could be developed to prevent these from occurring in the future. We discovered that data quality errors tend to fall into two categories:
Data entry (e.g., typos or mistakes made by the user when inputting the data)
Data processing (e.g., loss or duplication of data, misattribution, and other issues occurring when the data is being processed and manipulated)
Standard measures to counteract data entry errors such as logic checks at the point of entry, user training and BI/engineering team training were then put in place to minimise the chances of these errors occurring.
4. Automate process for error discovery
Once the approach was signed off, we worked with the data engineering team to automate the process of error discovery so that the quality of data can be monitored and the trends can be reviewed over time. To facilitate that, we developed an automated data pipeline that would run every day, detect erroneous records and write them into a table in the Trust’s database.
5. Build a dashboard
We then built an interactive PowerBI dashboard that allows operational leads to access this information, review existing erroneous records directly, and correct them. In addition to that, it provides high level oversight of the state of data quality in the Trust, as well as data quality trends, which is helping the executive team steer the Trust in the direction of complete, high quality PTL data.
6. Work with the team to develop internal processes
Upon the completion of the project, internal processes were put in place for dashboard maintenance and operational use. Every day, the data in the dashboard would get refreshed so that the operational teams can have the most up-to-date information and use it to correct the erroneous records. The teams would also meet every week to review trends and identify priority areas for data quality improvement
Demonstrating the value of elective orthopaedic hubs at the NOA awards
With over 750,000[i] people currently waiting for elective orthopaedic operations in England, there has never been a greater need for highly productive units working in partnership. Edge Health was therefore honoured to sponsor and present the Partnerships and Integration Initiative awardat the recent National Orthopaedic Alliance Awards event.
The winner of the award, South West Ambulatory Orthopaedic Centre (SWAOC) is the elective orthopaedic hub set up at the renovated Nightingale hospital in Exeter to deliver high-volume and low-complexity (HVLC) activity.
The SWAOC hub was formed from the national initiative to develop 91 hubs across the country and help drive down the backlog in elective orthopaedics. SWAOC won the award for its exceptional results, which included delivering over half (56%) of their activity as same day procedures – a rare, but critical achievement for managing limited inpatient bed capacity.
This outcome was driven by a clinical redesign of the facilities to best align with the hub’s goals and a multidisciplinary team that reviewed international best practice. To do this, the SWAOC team visited exemplar units, engaged with regional clinicians, and developed standardisation pathways of care to deliver better outcomes. As a result, fewer beds are taken up by patients recovering from surgery, reducing the burden on NHS resources more generally.
Edge health presenting the excellence in orthopaedics award in the ‘partnerships and integration initiative’ category to the south west ambulatory orthopaedic centre for a revolutionary collaborative approach to delivering orthopaedic surgery and tackling the backlog (download project poster)
Jonathan Howell, Consultant Orthopaedic Surgeon, Royal Devon University Healthcare said:
“This award and recognition by our peers of the fantastic results achieved by our multi-disciplinary team, has delighted all of us at SWAOC, and the many people in the wider Devon community who have contributed to this project. It is particularly fulfilling for us to have been recognised for our innovative approach to elective orthopaedics so soon after opening this year, and it is testament to the tremendous efforts of all those people who have given their precious time to work on this venture”
Jonathan Howell, Consultant Orthopaedic Surgeon, Royal Devon University Healthcare
The elective hub and HVLC programme
Since the start of the COVID-19 pandemic, there has been increasing focus on the elective care backlog that has continued to grow. A solution that emerged from GIRFT in 2021 was the prospect of establishing elective activity hubs, like SWAOC, to rapidly deliver HVLC activity.
Work undertaken by Edge Health to support this programme looked at the opportunity for these hubs, and the capacity required to meet the potential demand. As a result, the policy received over £1.5 billion of funding for the next 3 years and in the last 9 months, over 90 hubs have been set up and are starting to deliver results.
Some of the hubs, like SWAOC, have demonstrated rapid results and now provide a template for others to learn from and follow – both nationally, in the NHS, but also internationally.
What can other orthopaedic departments learn from SWAOC
It is clear that system working, collaboration, and the development of new pathways have been core to the success of SWAOC.
Mary Stocker, Consultant Anaesthetist, Torbay and South Devon NHS FT said:
“We are delighted to receive this NOA Excellence in Orthopaedics Award in recognition of the exceptional patient outcomes and innovative pathways delivered by the SWAOC multidisciplinary team. The volume of outstanding feedback we receive daily from our patients is a tribute to our team and the outstanding care they provide.
Mary Stocker, Consultant Anaesthetist, Torbay and South Devon NHS FT
This and SWAOC’s ability to deliver over half of its activity as “same day”, and with only 1% staying longer than 24 hours, has enabled the unit to achieve patient flow. This patient flow has enabled the unit to deliver highly productive results with minimal cost and, arguably more importantly, less demand on people.
Edge has already worked with GIRFT to create a dashboard that enables Trusts to track their HVLC activity. As a result, the 63 orthopaedic hubs already set up in England can identify key areas of improvement in real time that will bring their surgical outcomes in line with the high-performing SWOAC hub.
If you are interested to learn more about Edge Health’s work on HVLC pathways, and the NOA award, please do contact us directly at [email protected].
All of our analysis on the impact of Covid-19 on the NHS is shared here – this includes our regional tracker. For further information please contact George on 07980804956 or [email protected]
Published 16 April 2020
The latest data on deaths from Covid-19 suggests we are past the peak in the UK.
It is early days, and the NHS is still fighting active cases, but one of the next mountains to climb is the growing waiting list.
In January there were over 4.4 million people officially waiting for treatment – more than 700,000 of them have been waiting for longer than 18-weeks. These numbers are probably an understatement.
Given hospitals have been told to postpone non-urgent operations for at least three months, so without anything else changing the waiting time for treatment will be at least three months longer. That is before considering the impact of urgent cases.
Our modelling suggests that the median waiting time will increase from 8.5 weeks to 13.5 weeks and that an extra 2.7 million people will join the 4.5 million currently waiting for treatment.
This waiting list is a big challenge, particularly when front-line staff are recovering from the disruption of Covid-19 and need to maintain vigilance. Is it really going to be a return to business as usual to solve this problem?
“What many people don’t see if that AI is already part of the NHS… AI and other smart platforms are already helping us improve the services we deliver for the NHS, and ultimately, the individual’s patient experience” – fantastic coverage in The Mail on Sunday, featuring the DigitalHealth.London Accelerator and Edge Health! Read on!
”AI in the NHS Artificial intelligence is already being used across the UK. Gina Clarke looks at how it’s being implemented and the benefits to patients and practitioners. […]
SURGERY SCHEDULING: When it comes to planning surgical procedures, in order to minimise cancelled appointments, AI is helping NHS trusts such as South Tees to reduce waiting times. By using SpaceFinder, a product from Edge Health that can be implemented into existing software, the technology estimates how long a procedure will take and fits other surgeries accordingly â€” similar to the game Tetris. On average, up to two hours of operating time per theatre per day is currently unused, whereas this software can maximise the time. It also works to eliminate weekend procedures, which tend to cost more. However, it’s important to note that with the majority of today’s technology, humans still get the final say.”
Press Release: KSS ASHN finds that SpaceFinder delivered improved productivity
In July 2019, the Kent Surrey and Sussex Academic Health Science Network undertook an evaluation at Ashford and St Peter’s Hospital on the impact of SpaceFinder – a tool developed by Edge Health to improve hospital operating theatre productivity. They found that SpaceFinder delivered:
13.3% increase in surgical procedures per list
3.1% reduction in theatre use outside of core hours
Up to 7.1% higher theatre time utilisation
£330,000 of additional surgery within the first year
This builds on previous assessments of the impact of SpaceFinder, such as the £3 million saving that it helped to deliver at South Tees NHS FT by allowing them to turn off weekend working.
SpaceFinder has also been recognised by the CQC in one of its assessments: “The Trust evidenced new models of working using technology with the implementation of the ‘Space Finder’ tool to transform theatre utilisation. The trust demonstrated ‘Space Finder’ has delivered efficiencies, such as weekend work now almost being fully absorbed into weekday lists.”
Patients benefit from this new technology as SpaceFinder means that they wait less time for surgery, are less likely to be operated on at weekends, and have more choice over the scheduling of their operation.
SpaceFinder works by analysing detailed data on past operations to understand the key factors that determine operating time. This includes information on the planned operation, patient, surgeon, anaesthetist, operating team, and operating theatre. These data are used to accurately predict operating time, so that space in an operating list can be identified and filled. Or overruns identified.
SpaceFinder also proposed optimal operating lists that are tailored to the surgeon and hospital. This is done by creating lists that make the most of hospital resources, including the available operating time. As it is tailored, these lists are optimal and minimise lost time and cancellations that can occur if equipment are scarce.
Press release: Edge Health joins cohort 4 of the DigitalHealth.London Accelerator
Press release: Edge Health joins cohort 4 of the DigitalHealth.London Accelerator
Edge Health is proud to announce that it joins cohort 4 of the DigitalHealth.London Accelerator programme. The DigitalHealth.London Accelerator is a programme aimed at speeding up the development and scaling of digital innovations across health and care and pioneer their adoption by the NHS.
Across England, over 5 million people are waiting for an operation – almost as many people as there are in London. At the same time, hospital operating theatres often go unused due to poor scheduling. The complexity of modern scheduling requirements is not being met by the systems currently available in hospitals.
SpaceFinder is a software developed by Edge Health that uses advanced analytics to accurately predict operating times and propose optimal operating lists tailored to local conditions. These lists take account of all available information so that valuable theatre operating time is used effectively every day.
South Tees NHS Foundation Trust implemented SpaceFinder to put more activity into its core operating time. This allowed it to turn off weekend working. As well as being safer for patients, less frustrating for staff, it helped save £3 million. This innovative use of technology was well received by the CQC as “outstanding practice”.
Through DigitalHealth.London, Edge Health is looking to sped up the development and roll-out of SpaceFinder so that no patient ever must sit on a waiting list longer than needed.