Scott Fletcher
Chief Executive Officer
Scott has a proven track record of leading, growing and selling VC and PE backed businesses in the Life Sciences and Healthcare sectors. He had led 2 successful exits and the acquisition and integration of several businesses across UK, Europe and North America. As an analytical chemist, Scott spent many years working in the pharmaceutical industry developing new and novel drug products and medical devices.
The NHS prides itself on delivering the very best care for all, minimising harm and supporting recovery. But sometimes well-meaning risk aversion can lead to unintended negative outcomes. For example, evidence shows, and patients tell us, that real recovery happens at home and in the community. Yet a hesitancy to discharge people until there is little to no risk means that people are kept in beds for longer. This doesn’t work for anyone. Patients are out of work and their family support systems. Beds are kept busy so the acuity level for admission gets higher and higher. Budgets are not being used effectively. Out of area placements have risen exponentially. Staff are overstretched and mental health waning.
With an urgent need to relieve this pressure, could better use of data help promote a healthier attitude to risk? With the right data-driven approach, there is an opportunity to empower staff to better understand patient journeys and inform decisions that help patients back to homes, jobs and lives. Because sometimes ‘good enough’ can actually reduce harm.
Getting to the root of the problem
The NHS is an incredible machine that relies on an orderly escalation and deescalation of patients through admission, treatment, and discharge to maintain its efficacy. This flow, stepping down through severity of care, prevents harm by ensuring capacity for the most acute cases when they occur.
However, with limited budget and resources, the NHS is struggling to meet the demand of a growing population and changing healthcare needs, meaning increasing competition for a finite number of beds. In physical healthcare the existing bed base is being maximised by taking advantage of less invasive surgical methods and more day case procedures to reduce length of stay. Mental healthcare, however, has historically struggled with length of stay.
Despite significant service transformation in recent years, including budget and staff increases, the average length of stay for mental health services users has risen. High levels of occupancy leave little headroom to respond to patients in crisis, leading to increasing numbers of inappropriate out of area (OOA) placements.
OOA placements are seen as an indicator of struggling services and, despite a government target to eliminate them by 2021, figures hit their highest level in five years in February this year. While OOA placements typically only account for a fraction of all mental health bed use, they are phenomenally expensive and represent the tip of an iceberg. To tackle them we must look beneath the surface and concentrate on what is driving bed usage both up and downstream.
Risk aversion and bed usage
Challenges in mental healthcare are multifaceted, and the lack of uniformity between settings, providers and services can make it hard to pinpoint where bed usage is going wrong. However, reluctance to step people down to lower acuity care is a common issue across inpatient services. Risk aversion plays a significant role here, with clinicians erring on the side of caution and holding onto people for longer, despite feeling they may recover better at home.
The lack of a culture of trust between inpatient and community settings can exacerbate the problem. Budget cuts in social care and local authority services have reduced the availability of community services. Consequently, inpatient consultants can be reluctant to discharge service users to community teams where there are doubts over their ability to provide adequate 24/7 care. Trusts we’ve worked with that have a positive relationship between inpatient and community teams have an easier time admitting, treating and discharging patients, and see significant performance benefits as a result
Staffing challenges are also a factor. Whilst overall levels have risen, many of these staff are newly qualified or in new, unregistered roles. Combined with clinical level vacancies, this change in skill mix can lead to a more cautious approach to discharge, with staff feeling they lack the experience and support to step down care. High profile media attention when things go wrong only adds to their reluctance. Even experienced staff might avoid discharging patients for fear of having to justify their decisions later on. And, though the NHS is open all hours, in reality there can be an imbalance in staffing that hinders early discharge planning, causing an over-focus on immediate needs and further clogging the system.
So what can providers do to support effective decision making and give staff the confidence to move patients through to a lower acuity of care?
The role of data in risk mitigation
Multi-faceted problems require multi-faceted solutions. But with limited time and budget, it’s here that making better use of existing data could help focus scarce resources, in the right direction, for maximum effect.
In the current environment, most inpatient service providers are too busy with essential patient care to identify operational problems and lack the information at their fingertips to justify discharge decisions.
Data solutions can give them this visibility.
Locked in the wealth of data held in mental health trusts is invaluable information on patient journeys – for example, did someone leaving an inpatient service stay in a lower acuity setting, did they present in crisis, where are they on their recovery pathway? How many organisations are truly using their data to look at their pathways longitudinally? Interrogating this information and making use of the data analysis and reporting tools that are now available to us makes it easier and quicker for providers to see how their patient interventions are working.
They can pinpoint where improvements need to be made or identify where working more effectively with system partners could get better results and prevent service users bouncing between services. Productivity metrics can help them optimise resourcing, highlighting where staff allocations need changing to better match patient needs, or to cope with times of peak demand.
Such solutions can also incorporate decision support tools that crunch data on previous services users to evaluate the impact of different care approaches on outcomes. They can help to quantify risk and provide assurance to clinicians who might previously have said ‘I’m not prepared to do this, this is too risky’, to say, ‘Well actually, you can discharge this patient, we know the risks in their pathway and can mitigate them’.
It sounds like the perfect solution – however risk aversion is also a major hurdle in implementing new technologies. Most healthcare leaders agree that using technology is essential for improving process and performance in the NHS, yet they are also sceptical about its use. This often stems from the failure of improperly evaluated and tested solutions and reinforces that the technology is only part of the solution – people need to know how to use it. Tech companies must engage with staff, understand operating models and reinforce data observations with this frontline experience to build consensus and ultimately support change.
Looking to the future
To continue its important work as a taxpayer funded service without sacrificing it being free-at-the-point-of-use, the NHS must focus on maximising resources to minimise overall harm. This starts by working in a more joined up way between inpatient and community services, and building trust.
Technology can help us achieve this, but its rapid evolution can be off-putting for providers. Rather than focusing solely on new tech like generative AI, relatively simple data solutions offer the opportunity to address ‘low hanging fruit’ and take the first steps in building a strong culture of data engagement. As the NHS becomes more proficient, more advanced applications can be explored, unlocking the potential for better decision making and improving the experience and outcomes people can expect from healthcare.
