Category: NHS key areas

Addressing NHS Waiting Times Through Patient-Initiated Pathways

February 16th, 2024. Go to post.

As of November 2023, the NHS faced a significant challenge with approximately 7.61 million patients on waiting lists for various treatments. This figure underscores a critical issue within the healthcare system, highlighting both the clinical risks associated with delayed follow-ups and the operational strains on healthcare resources.

Addressing Waiting List Challenges with PIFU

The concept of Patient Initiated Follow-Up (PIFU) has emerged as a strategic response to these challenges. By allowing patients to determine the necessity and timing of their follow-up appointments, PIFU aims to enhance patient safety, optimise appointment scheduling, and reduce unnecessary follow-up engagements, thereby potentially decreasing waiting list volumes.

Despite the theoretical benefits of PIFU, there remains a lack of empirical evidence supporting its efficacy in practice. This, along with the ever-present challenges of changing existing pathways, means that many Trusts will miss the modest target of moving 5% of outpatient attendances to PIFU pathways, that NHS England set for March 2023 as part of the Elective Recovery Strategy.

The Role of DrDoctor and Key Findings: up to £167 million in System-wide Savings

In this context, DrDoctor, which oversees around 20% of NHS outpatient booking activities, including PIFU services, has played an important role. Through its operations across multiple Trusts, DrDoctor has gathered extensive data that, when analysed alongside Trust-specific data, offers insights into the potential health economic benefits of PIFU to inform increased usage and improvement of the service.

Edge Health was commissioned by DrDoctor to combine learning from this data as well as from interviews with clinical and operational staff involved in implementation at two large NHS Trusts to start evaluating this service delivery model. The report sets out the findings from data analysis, literature review and operational and clinical engagement into the potential real-world benefits, and best practice implementation of PIFU.

Key findings suggest that achieving the national target of a 5% PIFU pathway adoption rate could result in the saving of approximately 1,393,154 outpatient follow-up appointments annually, leading to an estimated system-wide saving of at least £167 million, based on 2020/21 figures.

Implementation Insights and Potential Impacts

Our report also provides details on how to effectively implement digital PIFU within Trusts, based on conversations with implementation teams. This highlights the types of specialties proven to be most successful to date, the conditions for the successful delivery of the roll-out of digital PIFU, key challenges services faced with implementation and what learnings they would give other Trusts at the start of their implementation.

The report also highlights the benefits to patients and the NHS of another form of patient-initiated pathway, Patient Initiated New Appointment (PINA). This is where patients referred to secondary care for an appointment are given control over whether they still require the appointment.

This report provides invaluable, real-world evidence highlighting the extensive value of implementing PINA and PIFU at scale within the NHS. It underscores the transformative role digital tools have in simplifying processes, modernising patient care and driving efficiency of system operations. We’re pleased to have worked with EDGE Health in producing this report and are excited about the wider impact this collaboration will have on the healthcare sector in reducing unnecessary follow-up appointments and tackling the backlog.

Tom Whicher, CEO of DrDoctor

From a waiting list perspective, PINA can help reduce the number of unnecessary first appointments at a Trust, in a similar way to PIFU. It is estimated that between 3-15% of patients on the waiting list do not need an outpatient appointment by the time they get contacted. By removing eligible patients who do not actually need a first outpatient appointment and are appropriate for PINA, our report found that the waiting list significantly decreases. This could mean a reduction in the waitlist by between 228,000 and 1,141,500 patients.

Therefore, the findings from our report can be used by Trusts to understand the potential of patient-initiated appointments (both PINA and PIFU) at their Trust and help them meet NHS England targets, while also driving down waiting list size and improving patient experiences.

Read Our Full Report Below:

Evaluating AI Implementation in the NHS: Skin Analytics AI-powered Teledermatology

February 5th, 2024. Go to post.

AI-Teledermatology: Innovating Skin Cancer Diagnostics

The healthcare system in England and Wales is experiencing unprecedented pressure due to the sharp rise in demand for dermatology services. With one in four individuals seeking consultation for skin, hair, or nail conditions each year, the need for innovative solutions has never been greater. The COVID-19 pandemic exacerbated this strain, causing a 30% drop in dermatology appointments during 2020/21 and a subsequent surge in patient referrals post-pandemic, with suspected cancer referrals rising 13% nationally compared to 2018. Rising volumes of urgent suspected cancer referrals have significant impacts for system sustainability – under a strained system, they correlate with higher volumes of patients breaching care standards, such as the 62-day treatment standard, as explored in a previous piece of work.

The potential of teledermatology, particularly AI-powered teledermatology, has been recognised as a promising solution to expand service capacity and ensure equitable patient access to specialist care. The Skin Analytics AI-Powered teledermatology for Skin Cancer 2-week-wait (2WW) Pathway was pilot tested across University Hospitals of Leicester (UHL) sites starting from March 2022. This collaborative project was designed to respond to the local need for improved patient access to dermatology diagnostics and the achievement of 2WW cancer targets.

Edge Health was commissioned by Health Innovation East Midlands (previously East Midlands Academic Health Science Network) to carry out an independent evaluation of the effectiveness of this pilot initiative. Leveraging our expertise, we gathered both qualitative and quantitative data from staff and patient surveys, as well as existing data from UHL and Skin Analytics.

A Novel Pathway

Our evaluation underscored the potential of AI-powered teledermatology. Despite being in its pilot phase, the AI tool demonstrated its capability to enhance patient access to dermatology services. While the initial benefit-cost ratio stood at 1.05, this figure doesn’t fully encapsulate the unquantified benefits, such as a reduction in biopsies, long-term care costs, and WLI clinics. Workforce costs were also front-loaded prior to capacity being fully utilised, leaving room for a higher benefit-cost ratio.

The current pathway model relies on second-reads to be performed on all AI-screened scans, with a further reduction in the potential benefit-cost ratio as well as increased pressure on clinical teams. In our evaluation, the AI outperformed documented clinical diagnostic standards[1], but our staff survey highlighted current reservations from consultants in dispensing of the second-reads altogether.

The evaluation also supported the health system through highlighting potential administrative challenges that scaled expansion would need to monitor for. These included timely booking of appointments for patients on the novel pathway, as well as ensuring that commissioning arrangements reflect the true costs of providing an innovative service – and are aware of the prospected savings.

Scenario Modelling for Future Savings

Looking ahead, we conducted scenario modelling to explore the potential for greater savings in the future. These scenarios hinge on reducing or removing the cost associated with the second read of dermoscopy images, leading to a benefit-cost ratio ranging from 1.3 to 1.9.

Our evaluation indicates that this novel pathway could be cost-effective in the long term. It could also offer considerable benefits to the wider Dermatology cohort, healthcare staff, and the health system if implemented at scale, with potential yearly savings across the Midlands ranging between £2.1M and £5.7M, depending on who performs the second read.

Recommendations for Enhancements

As part of our commitment to continuous improvement, we proposed several recommendations. These include streamlining administrative processes, evaluating the best option for lesion second reads and conducting further evaluations as the AI versions improve and more data becomes available.

Our work with Health Innovation East Midlands, UHL and Skin Analytics demonstrates Edge Health’s commitment to pioneering innovative healthcare solutions. Evaluating the effectiveness of new technologies such as AI-powered teledermatology is a fundamental step in improving services so that they are accessible, efficient, and patient-centred.

Our overall experience of working with Edge was very positive, and their analysis and evaluation process was robust and innovative. They handled challenges well and always sought a balanced solution with cross-stakeholder agreement. The Final Report was delivered on track and met the expectations outlined in the original scope and MOU.

Michael Ellis – Senior Innovation Lead, Health Innovation East Midlands

Key Successes

  • Conducted a comprehensive independent evaluation of the AI-powered teledermatology pilot initiative.
  • Identified potential for significant future savings through scenario modelling.
  • Proposed actionable recommendations to enhance the programme’s benefits and ensure long-term cost-effectiveness.
  • Highlighted the importance of considering administrative implications of implementing novel technologies.
  • Provided insights to guide future evaluations as AI technology evolves and more data becomes available.

This project was carried out in partnership with Health Innovation East Midlands

[1] Chuchu N, Dinnes J, Takwoingi Y, Matin RN, Bayliss SE, Davenport C, Moreau JF, Bassett O, Godfrey K, O’Sullivan C, Walter FM, Motley R, Deeks JJ, Williams HC. Teledermatology for diagnosing skin cancer in adults. Cochrane Database of Systematic Reviews 2018, Issue 12. Art. No.: CD013193.

A Data-driven Approach to Planning Radiotherapy Workforce Requirements

January 26th, 2024. Go to post.

There is no greater source of pressure in the NHS at the moment than staff shortages. Rising demand, growing complexity and lengthening waitlists, combined with high turnover, absence and staff leaving the NHS post-Covid, have created a gap between demand and supply of staff.

Understanding and responding to this gap is a complex problem across the health system. Doing so requires a detailed understanding of future workforce requirements and innovation in model and roles. By partnering with Dearden HR, award winning HR and OD consultants, we are able to combine our robust analytics and understanding of data with bespoke people and OD solutions.

West London, Surrey & Sussex Radiotherapy Operational Delivery Network

One example of our work together was with the West London Surrey & Sussex (WLSS) Radiotherapy Operational Delivery Network (ODN). The ODN, which comprises 4 radiotherapy providers, sought to understand their future workforce requirements and opportunities to innovate and implement a new workforce model to meet demand.


Our approach revolved around three workstreams. The first two supported the development of a rich evidence base, through modelling of future demand and activity and gaining a detailed understanding of the ODN’s current workforce status. These efforts formed the groundwork for assessing the future workforce requirement and developing an action plan for meeting this requirement. Our approach was designed to ensure that the final outputs are rigorous in detail and evidence, innovative in approach, built off existing best practice and co-developed with providers and ODN leadership.

The modelling was built on anonymised attendance-level data collected from each provider. This level of detail allowed for robust modelling of the workforce requirements of current and future activity, considering changes in complexity, treatment type and pathway. This was supported by workforce data and staff engagement, including a questionnaire and interviews to better understand each Trust’s workforce model, as well as staff motivation and job satisfaction at each of the Trusts.  This multi-faceted approach ensured a comprehensive understanding of the present workforce landscape and laid the groundwork for informed workforce planning and recommendations.

Future demand was modelled based on a range of scenarios, considering changing population, demographics, population health and cancer treatment. This modelling informed future workforce requirement scenarios. An interactive workforce planning tool was developed alongside the final report, enabling scenario analysis for future workforce shortfalls or surpluses based on Trust-specific assumptions.

“Partnering with Edge Health allows us to develop recommendations and an implementation plan which is based on clear and rigorous data analysis.”

Michelle Hodgkinson, Director, Dearden HR   


Based on the demand and capacity modelling and our understanding of current staffing levels, we calculated the additional establishment and in-post WTE required to meet the recommended level of staffing. The work also developed a series of recruitment and retention interventions, including regarding:

  • Apprenticeships
  • International recruitment
  • Active retention and support
  • Development roles
  • Flexible working

The combination of quantified workforce gaps and recommended interventions has provided the ODN and each Trust with a strategy for addressing future workforce pressures. This is currently being taken forward within the ODN.

Revolutionising Lung Cancer Diagnosis: The Economic and Clinical Impact of ctDNA Testing in the NHS

January 15th, 2024. Go to post.


In 2020, 37,211 people were diagnosed with lung cancer in England. 68% of this population is at an advanced stage and has limited life expectancy. People with advanced lung cancer have complex care needs and often experience high levels of GP appointments, hospital admissions and extended lengths of stay while awaiting diagnosis and treatment.

Timely genomic testing of the tumour can help identify individualised treatments, which can potentially markedly improve the quality and length of life. Delays in identifying specific gene mutations can result in missed opportunities for patients to receive targeted and more effective treatments, ultimately leading to worse outcomes and higher costs for health systems.

Liquid biopsy, a cutting-edge diagnostic method validated through numerous clinical trials, involves testing blood samples for biomarkers like circulating tumour DNA (ctDNA), among others, to detect cancer-related genetic mutations. This less invasive approach offers several benefits, particularly in vulnerable patients with advanced non-small cell lung cancer.

The NHS in England is working towards being a global leader in adopting liquid biopsy testing into a national health service. Recognising the importance of economic assessment and evaluation of the costs and benefits of broader ctDNA testing, Edge Health was commissioned by NHS England to undertake this work to support an ongoing national pilot involving non-small cell lung cancer testing.

Using health economics to understand benefits and costs

Our initial findings in the early phase of the health economics analysis of ctDNA testing combined academic methods with commercial insight and experienced understanding of how the NHS operates to assess the economic implications. This involved collaboration with clinical experts and synthesis of information from various other sources. As a new technology, our analysis considered various clinical scenarios and sensitivities for critical assumptions.

“Implementing ctDNA testing into the routine diagnostic work up of patients with lung cancer is a huge step forward to improving equity of access to state of the art genomic testing for our patients. This will allow patients to receive the best treatment possible for their condition. The input from Edge Health has been invaluable in mapping out a complex pathway, identifying options for ctDNA implementation and their associated cost benefits”.

Professor Sanjay Popat, Consultant Thoracic Medical Oncologist, Royal Marsden Hospital

Outputs from the initial analysis were extrapolated more generally with national data, which helped identify the potential future costs and benefits.

In the context of stage III and IV lung cancer, from early analysis, the application of ctDNA was found to deliver significant benefits relative to its costs. This finding was primarily driven by ctDNA testing enabling earlier blood testing and potentially avoiding tumour genomic testing, which supported patients to access targeted treatments earlier and more consistently – lowering broader system costs. In the next phase of work, pilot data will be analysed to validate these preliminary findings to support the commissioning of the ctDNA test on the genomic national test directory.

Moreover, ctDNA testing is expected to improve equity in genomic testing access substantially, expanding coverage over a broader spectrum of gene mutations and ensuring the inclusion of patients for whom adequate tissue biopsies might not be viable.

Genomics vision

Ultimately, incorporating the latest genomics advances into routine healthcare will help deliver the UK government’s vision in “Genome UK: the future of healthcare”.

“The current work of the ctDNA pilot aligns perfectly with the Genomic Medicine Service goals of delivering equitable genomic testing for cancer patients through accessing cutting edge technology and science.  This technology will hopefully, if commissioned onto the national test directory, ensure that clinical services can make better-informed decisions faster, have access to precision treatments which will improve patient outcomes, ultimately leading to more efficient use of NHS resources. The work from Edge Health is vital in helping to demonstrate that this advance in care is also economically viable”.

Paul Ryves, Programme Director, North Thames Genomic Medicine Service Alliance.

Contact us to learn more about our approach and how we can help you.

Routine orthopaedic procedures are more complex than ever before in the NHS

September 18th, 2023. Go to post.


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.

  1. Hospital Episode Statistics (HES), a detailed dataset containing clinical, demographic, and patient information.
  2. 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.

Figure 1. Features used to estimate clinical cost from HES data.

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.

  1. Increased cost and resourcing requirements should be reflected when creating activity plans. This will affect trust, care system and specialty managers with limited budget.
  2. 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.
  3. 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.
  4. 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.


  1. ↩︎
  2. ↩︎
  3. ↩︎
  4.,from%2016.4%25%20to%2018.6%25 ↩︎
  5.,week%20programme%20prior%20to%20surgery ↩︎

Imaging Productivity: Harnessing RIS data to meet reporting targets

June 8th, 2023. Go to post.

Diagnostics is moving into focus

The focus for efficiency gains has traditionally been on theatres, inpatient and outpatient activity and more recently the growing elective backlog. Diagnostics, however, have acquired a new emphasis since COVID. This is because significant backlog in diagnostics is causing delays in finding cancers (you can read more about this on our blog).  

As a response, NHSE has included diagnostics activity targets in the NHS Constitution, stating that all tests must be performed within 6 weeks from request. This puts pressure on trusts to understand their testing activity, capacity and bottlenecks in imaging reporting that cause downstream delays in the 18-week referral to treatment (RTT) target.

Trusts have not historically analysed diagnostics data in depth

Gathering these insights requires analysis and data flows which are not yet set-up well across Trusts. Data from radiology information systems (RIS) has not been used as extensively in the past and existed in lower quality than, for example, theatre data. In this context, Trusts now struggle making sense of their imaging data to action NHSE targets.

We were recently asked to support a large specialist NHS Trust in helping with this.

The ask: time-sensitive solutions to guide management

We did this in three stages:

  1. Analyse national data to get a high-level picture.
  2. Engage with team on the ground to understand what actionable insights are needed where and why they are not provided.
  3. Deploying expert clinicians and analysts to provide the insight in a repeatable way.

We outline each of the below in turn and give some detail on the issues under the hood.

First: Public data

First, we explored publicly available data on the Trust’s diagnostics to form the start of meaningful conversation and gain a high-level understanding of some of their challenges. The two charts below showed that our client (Comparator 1 in the chart on the left) had above average waiting times for a scan to be reported, following testing. The time between testing and reporting had also seen a significant increase in 2022/23 compared to 2019/20, particularly for MRI, Nuclear Medicine and Single Photon Emission CT.

Second: Working with team on the ground to understand the problems

We then sat with stakeholders to map the imaging data journey at the Trust and uncovered the key issues within it (outlined below).

Issues we found were the below:

  1. Complicated set-up: Before an end-user could reach any insight, four pieces of software needed to interact: a requesting software like ICE, a RIS software, a PACS software and finally a BI software, QlikView in the client’s case. All insights needed to wait till the analytics team had curated the data.
  2. No quick way around it: Managers trying to extract data from RIS directly were faced with a complex interface that was both hard to work with and at risk of producing unreliable metrics. This step was incredibly time-consuming for managers, adding to undue stress.
  3. Lack of resources: There were no dedicated imaging analysts at the Trust, which meant the imaging team had to compete with other teams to get the insights they needed from the busy BI department.
We supported the trust outlining a variety of solutions, including:
  • Increasing workforce, such as a specialist PACS or analytics team member.
  • Changing work practices, such as setting a cap on highly time-consuming MDT requests to focus on internal workload, and upskilling radiographers to report imaging.
  • Upgrading software to one that included basic analytics, timed with a contract soon to expire.

In order to tie the department over with an urgent need for insights, we also delivered a fast turn-around reporting solution ourselves, embedded in their current BI environment.

Third: Delivering a trusted solution

We were onboarded on the Trust’s system to work within their environment and built a relationship with the BI and analytics team to ensure seamless knowledge transfer and accuracy of outputs.

Engaging with stakeholders also helped build trust in the outputs and ensure that it was truly useful to the team and met expectations.

Early draft of one of our reporting interfaces showing high-detail overview of reporting activity by radiologist and imaging modality, and reporting waiting times at a glance.

By the time the tool was ready to be shared Trust-wide, it had received the seal of approval from the imaging manager, the clinical director, and the BI lead. The final product was fully handed over to the Trust’s BI team to use as a starting point for more analysis and maintain as required in the future.

Specifically, it provided a high-detail overview of reporting activity by radiologist and imaging modality, and reporting waiting times at a glance.

This is enabling the Trust to:

  • understand pressures on the imaging department
  • manage workflows more effectively
  • back department investments and business cases with evidence
  • improve their performance against NHS diagnostic targets.

Improving Cancer Outcomes – Why ICSs Must Tackle Health Inequalities

June 1st, 2023. Go to post.

There is a recurrent emphasis on the need for Integrated Care Systems (ICSs) to address health inequalities, as highlighted by media outlets, conferences, and reports.

Addressing these disparities is a monumental task, especially for the newly established ICSs, which have been tasked with not only establishing new governance and strategies but also tackling an elective backlog and long-standing health concerns like health inequalities.

One crucial area of focus, particularly in relation to the Core20Plus5 mandates, is cancer, as we are aware of inequalities in access impacting diagnosis and survival rates. The ambitious objective set out by the NHS Long Term Plan is to diagnose 75% of cancers at Stage 1 or 2 by 2028.

Lung cancer, where 64% of patients receive a diagnosis at stage 3 or 4, is an excellent example that underscores both challenges and opportunities for ICSs.

Why avoiding emergency diagnoses is key

We examined publicly available data on lung cancer care. Patients referred by a GP are more likely to be diagnosed at an early stage than those in emergency settings.

This relationship can be seen by comparing NHS clinical commissioning groups (CCGs), where a 10% increase in GP diagnoses is associated with a 3% increase in early diagnoses (stages 1 and 2), when adjusting for confounding factors, as shown in Figure 1.

Figure 1. Source PHE 2018

Since patients are over 3 times more likely to survive more than 5 years when diagnosed at stage 1 compared to stage 3[i], detecting cases via referrals from primary care has a direct impact on lowering lung cancer mortality rates associated with a late-stage diagnosis.

Diagnosis RouteStage 1Stage 2Stage 3Stage 4
Primary Care21%10%25%44%
Emergency Department10%5%14%72%

Table 1. Source NCRAS 2015-16

Reducing variation in primary care referral rates

The challenge, however, lies in the unequal volumes of lung cancer referrals made in primary care, which vary dramatically across NHS regions. We have used Public Health England data and machine learning approaches to uncover the relationship between the number of GP referrals and the percentage of all lung cancer cases diagnosed from these referrals.

As seen in Figure 2, there is a clear positive relationship between the volume of referrals from primary care and early diagnosis, which is particularly strong for areas with low referral volumes.

It follows that if GPs with low referring rates could be supported increase referral volumes, there will be a high impact in driving earlier diagnosis and improving survival rates. This means that increasing referral rates would be very material for the NHS and its patients. In fact, if all ICSs were able to bring all the lowest referring GP services in line with the bottom quartile, as shown in Figure 3, we would expect 700 extra early diagnoses and 100 lives saved per year across the country.

Figure 2. Source PHE, 2018
Figure 3. Source PHE, 2016

How these findings turn into practical implications for ICSs

Variation in urgent suspected cancer referrals and early diagnosis rates is likely a combination of both GP organisation/behaviour and broader patient behaviour. For the former, it is well known that there are pressures on GP numbers and overall workload, which will impact access locally.

Nonetheless, there will be opportunities for ICSs to surface data on variation in cancer referral rates and work with practices to understand variation and support where necessary.

ICSs can also lead improvements by understanding how their local population, demographic and health system factors are influencing access. Although this highlights the complexity of the challenge, it also offers multiple sources of opportunity for systems.

In our experience, some of the key actions for ICSs to address the above are:

  • Involve primary care networks (PCNs) and cancer alliances early into conversations about improving cancer detection – we are currently working with a cancer alliance on data-driven research to better understand the drivers of variation in the detection rate and the most effective interventions for addressing them.
  • Provide practices and PCNs with tools to better understand their local population and their health needs (see here for a population health management dashboard we developed for Surrey Heartlands).
  • Plan adequately for workforce, particularly in primary care, to make sure there is enough capacity to boost referrals and avoid workforce overwhelm. Given the falling numbers of full-time equivalent GPs, this is a priority area for ICSs and nationally.
  • Assess secondary care diagnostic capacity, including modelling demand and capacity and promote system-wide initiatives such as new community diagnostic centres, implementing rapid diagnostic services and supporting mutual aid between trust, as we have discussed previously.

As the landscape of healthcare continues to evolve, ICSs have a crucial role to play. The responsibility lies with them to implement innovative strategies, utilise data-driven research, and ensure a robust primary care workforce.
With a concerted effort towards these goals, ICSs have the potential to significantly influence early cancer detection rates and, ultimately, patient survival.

[i] Characteristics of patients with missing information on stage: a population-based study of patients diagnosed with a colon, lung or breast cancer in England in 2013. C Girolam and others BMC Cancer (2018). Volume 18, Page 492

Why We Need to Start Unlocking Change Using Cancer Data Now

May 18th, 2023. Go to post.

We can all agree that cancer does not go on holiday. Yet during the winter months, referrals for suspected skin cancer in England decline steeply.

The National Health Service (NHS) collects extensive data that presents a golden opportunity for improvement and targeted interventions. For instance, by examining the data on skin cancer referrals, we can identify a long-standing pattern that presents a significant opportunity and exemplifies the potential of routinely collected data to enhance outcomes.

In the case of skin cancer, this opportunity translates to 170 lives a year that may have been saved through earlier cancer detection.

Skin cancer referrals: unlocking opportunities through a 10-year trend

The NHS Digital Cancer Waiting Times records provide valuable insights into skin cancer referrals. A simple glance at the time trend reveals a stark cyclical pattern.

The difference between the lowest point in referrals in January and the peak in August is astonishing, with August witnessing a 60% increase compared to January.

If we were to expect referral volumes to be relatively constant across the year, 36,000 patients might have presented sooner than they did in 2022. Given the skin cancer conversion rate of 8%, that’s nearly 3,000 potentially delayed diagnoses.

Moreover, the number of 2WW referrals aligns rather consistently with the number of patients awaiting cancer treatment. Therefore, fewer referrals are a result of fewer cancers presenting and being detected, rather than an artificial summer spike in referrals.

It is not news either – the pattern was present in 2016 and is just as prevalent today as it was then. This is an area that would benefit from targeted intervention.

A Chance to Improve Patient Outcomes

The decline in winter referrals for skin cancer likely occurs because people tend to notice skin changes less often during this season, and others may also point them out less frequently (for instance, as suggested by Walter et al. ). This effect has been observed for several years, not only in the UK but also in countries like Italy and France.

What is notable about the UK, however, is that it lags behind much of Europe for cancer survival rates – this includes skin cancer, though to a lesser extent, given the generally higher survival rates compared to others.

Early detection represents the greatest opportunity for addressing this disparity. Patients who delay their presentation to a GP until the summer may be diagnosed with cancer at a stage later than otherwise.

While skin cancer survival rates are relatively high, late-stage detection significantly reduces chances of survival. For patients diagnosed at stage 1 cancer (55.5% of diagnoses), the 5-year survival rate is 100%. This, however, drops 84% for stage 2 (21% of diagnoses) and 73% for stage 3 (8% of diagnoses). Detecting melanoma at stage 1 versus later stages could save 560 lives for every 10,000 patients.
For 2022, that means an extra 170 lives could have been saved out of the 3,000 potentially delayed diagnoses.

Addressing Service Challenges

The surge in summer referrals for skin cancer also strains the capacity of healthcare providers, leading to delays in diagnosis and treatment for all dermatology patients. This issue has become even more significant in the aftermath of the pandemic, as healthcare services struggle to cope with mounting waiting lists.

The following chart highlights this challenge – as the volume of 2WW referrals increases, so do the 62-day target to treatment breaches. Although the time lag between the two is not substantial, it has widened since the pandemic, likely due to the extra burden posed on services by the elective backlog.

Patients referred just before the peak experience the most significant impact, as the capacity for 2WW referrals competes with the capacity for treatment. This indicates a healthcare system under pressure, where there simply isn’t enough capacity to handle a sudden rise in referrals. To address this issue, targeted solutions are needed.

What can we learn from this?

There is a strong case for gaining more insights across various cancer types, examining inequalities, geographies, pathways, and populations to align them with the Core20Plus5 priorities.

This knowledge can help to focus on a broader range of interventions and measure their impact.

For skin cancer, two clear opportunities emerge:

  1. Implementing winter skin check campaigns, akin to successful breast cancer awareness efforts. Targeted outreach could encourage earlier presentation, improving outcomes.
  2. Provider strategies to manage summer surges, such as Teledermatology and cross-site collaborations. New approaches may expand capacity for minor procedures and biopsies, speeding up diagnosis and care.

Data-driven insights can focus and maximize initiatives by revealing where needs and inequities lie. They also offer opportunities to monitor progress and assess effectiveness.

Learning to harness information will be crucial to the future of the NHS. The skin cancer example serves as a testament to how data can uncover life-saving possibilities and point the way toward realising them.

Elective Recovery: understanding targets and finding opportunities to increase activity

April 6th, 2023. Go to post.

Elective recovery targets – a confusing landscape

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.