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.

Developing a System Intelligence Specification in South East London

December 18th, 2023. Go to post.

There are unprecedented challenges facing health, care and communities, and a need to change how we work in response. There is huge potential in the data and capabilities already available within systems, and opportunities to address growing activity, financial and workforce pressures by making best-use of limited resources.

It is critical that systems have a shared vision and understanding for how the effective use of business intelligence and analytics can improve health outcomes

This vision must encompass improving outcomes in population health and healthcare, tackling inequalities in outcomes, experience and access, and enhancing productivity and value-for-money.

Wordcloud from System-wide Analytics Survey

The System Intelligence Specification for SEL ICS was co-developed with a wide range of leaders and stakeholders across the system

This included individuals from the SEL Integrated Care Board, Place, local Councils, acute, mental health, primary, community and social care providers, and other clinical networks and partners leading innovation in the system. Edge Health partnered with Public Private Ltd (PPL) to gather experience and insight on current requirements on business intelligence, articulating the future for analytics, and identifying the gaps.

The System Intelligence Specification articulated what South East London will be able to deliver through the better use of information and data, supported by key use case examples

The specification aimed to be ambitious but pragmatic, focussing on key value-add use cases and real-life examples to describe what collaborative working principles, skills and data are required to support enhanced working at all system levels.

This led to short and long-term recommendations to the SEL Board, and plans to deliver on these strategic commitments

The work and engagement provided collective clarity and a focus on opportunities that should be developed as a system. It provided a starting point for workshops that were held to formalise a digital and data enablement group in SEL, bringing together system leaders to turn data into insight into action, and impact individual patient outcomes.

Case Study: Evaluation of the Mental Health Urgent Assessment Centre at LPFT

July 17th, 2023. Go to post.

Edge health led a health economic evaluation of the Mental Health Urgent Assessment Centre (MHUAC) within Lincolnshire Partnership NHS Foundation Trust (LPFT), working closely with both the project team at LPFT and the East Midlands Academic Health Science Network (EMAHSN).

Working in partnership with Edge Health has really added value to the evaluation process, they have been fantastic with regards to communication. It’s obvious from interaction with them that they have a keen interest in the project and really have been supportive with regards to their view on difference our new service is making.

Simon Ringland, Business Manager – Adult Inpatients & Urgent Care, Lincolnshire Partnership Foundation Trust

Innovative support for patients in a mental health crisis – the Mental Health Urgent Assessment Centre

People in a mental health crisis are at their most vulnerable. It is essential that they receive the care and support they need as quickly as possible, in a place where they can feel safe, and are cared for by people who understand their needs.

Patients requiring emergency mental health services often present to the Emergency Department (ED). With EDs under extreme pressures, waiting times for mental health patients attending ED have increased substantially. The busy, often noisy and sometimes crowded ED is also not considered the best environment for patients in mental health crisis to wait to be seen.

To address the needs of patients in mental health crisis who attend ED, Camden and Islington NHS trust implemented a Mental Health Assessment Centre to offer support in a different way. This involved the mobilisation of a Mental Health Urgent Assessment Centre (MHUAC), to offer those that were medically fit a service that did not require attendance at ED for support. The service offered rapid assessment of mental health need and an additional place of safety in an environment that was appropriate and calming. The benefits of the service were identified as lessened 12-hour breaches in ED, decreased footfall through ED, improved patient and system partner satisfaction.

Similarities between the challenges faced by Camden and Islington NHS trust and Lincolnshire Partnership Foundation Trust with mental health crisis care led to the decision that Lincolnshire would benefit for a service similar to Camden and Islington’s Model.

A rigorous evaluation methodology

We conducted an independent evaluation of the measurable impact of the MHUAC at LPFT on patients, staff, and the health system using data from the trust, a patient and staff survey designed and deployed by our team, and several patient and staff interviews. This data collection allowed us to determine the costs and benefits of the pilot and the potential annual savings if the pilot were to expand across the Midlands.

We took the following approach to achieve this:

  • mapped out a patient journey, identifying the changes in behaviour brought about by the new service delivery model;
  • using this journey, summarised an “impact pathway” to set out a long-list of potential benefits across a number of different stakeholder groups;
  • quantified and valued these benefits, based on available data, literature and stakeholder engagement; and
  • scaled these results to give an indication at a Midlands-wide scaling of the potential costs and savings from wider roll-out of the pilot.

The work involved a visit to the site at Lincoln County Hospital where we spoke with both patients and staff about their experiences and views on the new service. This work helped guide the analysis, informed our findings and enabled our team to have a deep understanding of the service.

Project outputs included clarity on the big-ticket drivers of benefit and value delivered by the MHUAC and a clear, impactful and robust estimate of the savings delivered to health systems, delivered within the client’s timeframes.

Impactful outputs

Our analysis demonstrated that the innovative service delivery transformation has been incredibly well-received by patients and all staff involved in the mental health crisis pathway, with approximately 85% of both staff and patients suggesting this is a better alternative to ED for patients in mental health crisis.

Alongside the extremely positive feedback from staff and patients, there is also evidence to suggest that this pilot has been cost effective. So far, this pilot has seen measurable benefits, such as, a reduction in inpatient attendances (£789,239 saved) and relapses (£61,473 saved). When scaled across the Midlands region, these benefits could reach over £14.4 million annually.

Therefore, we reported the MHUAC has a benefit cost ratio of 3.5. This ratio may also still improve with time, with a number of significant benefits, including societal benefits, not possible to quantify at this early stage of the pilot.

Given the significant potential of this initiative, it is important the right processes are in place to maximise the benefits it delivers. To aid with this, the evaluation also generated several considerations to improve the service both at the Lincolnshire site and to aid other Trusts if the MHUAC were to expand to other sites.

The evaluation report is now helping to drive conversations locally to recommend the MHUAC initiative to other local organisations. The report has also helped the AHSN to robustly articulate the success of the project which they are now planning to submit to the national Health Service Journal awards.

Case study: Evaluating the benefits of integrating chemotherapy patient management apps

July 10th, 2023. Go to post.

Challenges in the Existing Healthcare System for Chemotherapy Patients

Cancer patients undergoing chemotherapy have to navigate a complex healthcare system at a particularly stressful point in their lives. Various patient management apps exist to support both patients and providers with this treatment pathway. However, a lack of a single source of information disadvantages both patients and Trusts.

Integrated Solutions for Patient Management and Prescribing Process

In response to this, the industry leader in electronic chemotherapy prescribing developed a product that integrates all aspects of patient management from referral to discharge and simplifies the prescribing process for healthcare professionals. Additionally, another provider created a patient-facing mobile app that brings disparate pieces of information from across the healthcare ecosystem together and delivers personalized support for cancer patients.

A typical Trust will treat between 1,200 and 1,500 new patients with chemotherapy each year. As such there are significant benefits to integrating these two patient management solutions and offering a bundle for purchase by acute providers. Edge Health was commissioned to deliver a report on the potential impacts of the integration. Through a review of existing literature and clinical engagement, we assessed the wide range of benefits throughout the patient journey. By quantifying some of these benefits, we sought to highlight the potential magnitude of the advantages for both Trust’s finances and patients.

Our Analysis of Impacts and Benefits of patient management solutions

Positive Impacts on Patient Care and Risk Management

Many of the identified benefits are felt by the patients themselves. The integrated app and system facilitate the delivery of optimal patient care and minimise chemotherapy treatment’s risks and side effects. The advantages of this integration appear to be most material for patients who may require changes to their treatment, due to adverse reactions or toxicity, or for the rarer cases of more severe illnesses such as colitis and neutropenic sepsis.

Financial Benefits to the Healthcare System

There are also clear and direct financial benefits to the NHS. Chemotherapy drugs are expensive and waste is a substantial issue, whilst the costs of treating patients who develop more significant illnesses during their treatment can be very large. Through accurate capturing and sharing of patient-reported outcomes, the integration contributes to cost savings by minimising the expenses associated with treating such complications or illnesses.

The integration of chemotherapy patient management apps offers significant benefits to both patients and healthcare organizations. By streamlining the treatment process, improving patient care, and reducing financial burdens, this integrated solution has the potential to enhance the overall quality of care for cancer patients undergoing chemotherapy. Acute care providers can leverage these apps to optimize their treatment protocols and improve resource allocation, ultimately leading to better patient outcomes and more efficient healthcare delivery.

“How many beds?”: Enhancing planning with bed requirement simulations

July 3rd, 2023. Go to post.


More than any other, one question we repeatedly get asked is “how many beds?”. Whether planning, improving patient flow, speeding-up discharge, producing business cases or responding to Covid-19, bedded capacity is frequently the biggest factor affecting both efficiency and outcomes. Robustly analysing patient flow and bed utilisation can drive effective decision-making and can facilitate future planning.

Edge Health has been engaged in helping multiple NHS Trusts to forecast their bed requirement and analyse the drivers of bedded pressure to support planning.

Mitigating risks and optimising bed planning

While monitoring bed requirements relative to the Trusts’ capacity is crucial, it is equally important to understand the underlying factors driving the demand for beds in a hospital. Taking this into account, we identify primary drivers of bed demand using detailed patient and ward level data to simulate bed requirements in an NHS Trust. These scenarios have been instrumental in aiding the planning of bed requirements in the Trust as they provide useful insights for effectively managing the Trust’s capacity.

It is very important to recognise the significance of understanding the variation of bed occupancy for the efficient calculation of the monthly bed requirements of a Trust. Hospital bed occupancy varies by minute and hour or each day – particularly for wards with short length of stay and quick turnaround times. Due to this variation, simply calculating the average number of occupied beds at the end of each day can misrepresent average occupancy levels and be unreconcilable with the experience of ward staff.

Variation in hourly bed occupancy over time

Our modelling approach

Detailed patient level data forms the basis of our analysis. To further understand the Trust’s capacity, we’ve also engaged with the staff to dive deeper in the wards structure and capacity, as well as any potential future capacity changes (including opening/closing of wards).

Utilising the available data, the key steps in our methodology approach are:

  1. Calculating total number of occupied beds using hour-by-hour patient level data, accounting for the variation in hourly data.
  2. Using the detailed ward allocations, aggregating the data on a division/ward/specialty level.
  3. Exploring requirements for achieving different levels of target occupancy.
  4. Creating multiple simulation scenarios to explore critical drivers of demand:
    • Variation and impact of length of stay.
    • Impact of ‘medically safe for transfer (MSFT)’ patients on capacity.
    • Effects from changing numbers of elective and non-elective admissions.
    • Influence of interventions like virtual wards.

Key insights

Employing a flexible modelling approach enables us to gain valuable insights and understand crucial aspects related to bed planning in a Trust. The main advantages of our approach include:

  • Capturing the relationship between key variables in the analysis and measuring their influence.
  • Quantifying the impact of areas of uncertainty in bed planning.
  • Leveraging the potential outcomes of interventions to develop effective strategies and optimise resource allocation.

This modelling approach serves as a powerful tool in aiding bed planning and driving critical strategic decisions within the Trusts.

See more examples of our work on bed modelling here:

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.

Elevating Performance and Driving Clinical Excellence: the Discharge Pathways Model Analytical Tool

May 25th, 2023. Go to post.

As the NHS grapples with ever-growing demand for secondary care from the elective backlog and aging population, establishing an efficient patient flow out of secondary care is fundamental for alleviating system pressures.

Minimising acute capacity required for delayed discharges and ensuring patients have the right level of support available to them upon discharge, at home or in a community bed, will not only reduce costs for the NHS and free up the resources for those who need them most, but also help achieve better outcomes for patients.

The importance of access to accurate and up-to-date data in trying to accomplish this is paramount.

Answer the right questions

Assessing the level of demand, identifying system bottlenecks, and linking local practices with patient outcomes are all crucial undertakings on the path to better managed care.

The important questions like “How many patients are expected to be discharged into the community?”, “What causes the majority of delayed discharges” or “What can I learn from my peers who are performing better?” need to be carefully considered and answered on both system and national levels.

Edge Health has been commissioned by NHSEI to support them in tackling the complexities of the interface between secondary and community care and improving the patient flow.

Working with a multi-stakeholder group, including academics, clinicians and system leads, and in collaboration with the national rehabilitation team, we have developed a Discharge Pathways Model Analytical Tool, hosted on the NHS Foundry Platform, that facilitates access to the most up-to-date data that can be used to address those questions.

Benchmarking interface, part of the Discharge Pathways Model Analytical Tool

A one-stop place to benchmark, learn, and plan

The tool allows systems to benchmark their performance against their peers to identify areas of success and avenues for improvement.

It opens up a conversation around what can the systems learn from each other’s experience and provides crucial insights to the national team, informing a larger clinical effort to develop best-practice for care in the community.

Scenario modelling capabilities for effective bed planning

The modelling element of the tool allows the users to explore different models of care that can be implemented and thus support the planning activities for this winter and beyond.

The tool is now live and accessible to users across all the 42 systems, as well as the regional and national users.

Edge Health are a specialist UK healthcare analytics consultancy that use data and insights to improve the delivery of health and care services, so that better outcomes can be delivered more efficiently.