ehospice is pleased to publish a paper by Dr Emma Hodges, Group CEO of St Giles Hospice, which explores how the need for Adult Specialist Palliative Care in three settings – inpatient beds, community nursing and hospice at home – might be calculated.

Emma presents an excel based model which utilises local, regional and national data in order to provide a best estimate of demand at Primary Care Network level. She also identifies challenges and limitations of her approach and she uses a fictional PCN by way of illustration. She recognises that this model does not attempt to include the broad totality of services provided by most hospices.

Assumptions are identified and explained, and the model allows for local variations and increased demands. As such it could become a much-needed resource to help facilitate commissioning. Its use will also enable trustees and staff to estimate the levels of unmet need in their own communities and plan accordingly.

While not being peer reviewed Emma has consulted with colleagues and published research has been used to help direct thinking. This paper, while in many respects being an ongoing work in progress, could well impact on the current and future planning and delivery of hospice palliative care services across the UK.

ehospice looks forward to publishing any future comments / discussions / thought pieces triggered by this paper.

If you have a paper on any aspect of Hospice & Palliative Care which you would like to see published on ehospice then please contact the UK editor at info@ehospice.com

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A UK population health approach to quantifying adult specialist palliative care

Abstract –

This paper provides a practical solution in addressing how to quantify the requirements for specialist palliative care (demand). It describes an excel based model utilising local, regional and national data in order to provide a best estimate of demand at a Primary Care Network level.

The paper recognises the challenges and limitations of such an approach and works through a fictional primary care network in order to illustrate how the model can contribute to the planning assumptions for both specialist palliative care providers and the wider system.

The scope of the model described below is specialist palliative care demand for inpatient beds, community nursing and hospice at home. It does not seek to report on hospices provision of a wide range of other services to an increasingly diverse group of patients or to undermine the holistic nature of care.

Background

The definitions of palliative and end of life care create many challenges for providers and commissioners. The interchangeability of terms is confusing creating barriers to care and challenges in the integration of services (Russell, 2015). Whilst there is data on how many people might be in the last twelve months of life, and data on how many people would benefit from palliative care, when it comes to quantifying how many people might require ‘specialist input’, the data is scarce.

The first challenge of course, is to define ‘specialist palliative care’. In 2012 commissioning guidance was produced to define specialist palliative care. The resulting definition was ‘the active, total care of patients with progressive, advanced disease and their families. Care is provided by a multi-professional team who have undergone recognised specialist palliative care training. The aim of the care is to provide physical, psychological, social and spiritual support’ (Tebbit, 1999 cited by Association for Palliative Medicine, 2012), p. 6).

The question of what hospices are and who they care for is also confusing. Many hospices are independent charities, primarily charitably funded, with variation across organisations adding to the challenge for emerging Integrated Care Systems and a desire for standardisation. Hospices have been criticised for the ongoing dominance of cancer patients in comparison to other disease groups (Leadbeater and Garber, 2010; Hospice UK, 2013; Marie Curie & Alzheimer’s Society, 2015; Hospice UK, 2015; Hospice UK, 2017). However, the long history of hospices in caring for people with cancer will mean that referrers are more confident in referring people from this patient cohort in comparison to others where there are less well defined pathways (Pooler et al 2007, Selman et al 2007). In addition, lack of resources have constrained hospices’ ability to meet local demand and adequately address the challenges of inequality of access.

The majority of palliative and end of life care is provided by primary care, community services and acute providers. With the specialisation of palliative care in 1987, many hospices carved out a ‘niche’, focusing on those patients requiring a multidisciplinary team to address complex needs with referrals coming from other parts of the NHS where the referrer felt additional support was required. Pathways and access to specialist palliative care and therefore hospice care remains less well defined for non-malignant disease meaning the inequality of access remains (Tobin, et al., 2021).

Data from the Cicely Saunders Institute provides insight into the numbers of people in the UK dying and suggests that the pandemic has accelerated this demand (Cicely Saunders Institute, 2021).

However, quantifying those who require ‘specialist palliative care’ is unclear creating ongoing challenges for hospices in articulating the funding required to deliver care from a population perspective.

The Population Based Approach for Quantifying SPC tool has been developed using Microsoft Excel to consider demand for specialist palliative care alongside workforce and finance modelling. It only models for three key service areas: beds, specialist palliative care nurses in the community and hospice at home (specialist healthcare assistants providing home visits). This is not to say that hospices do not contribute to and/or offer a wide range of services, however, they are not represented by this particular article.

Where possible parameters used within the model have been validated and tested in several ways and this will be explained step by step through the next section of this paper.

The SPC Demand Modelling Tool in Practice

Developing a tool for quantifying specialist palliative care should start from a population basis, and this model uses the GP’s list size at Primary Care Network level. To determine how many people on the GP’s list might be in the last 12 months of life, the 1% indicator is used based on work by Dying Matters (Dying Matters, n.d.). 11% of that number are then excluded as they relate to sudden death (The Strategy Unit, 2018). This then provides a number of people who might benefit from some form of palliative care.

A worked example will be included in each section in italics.

For ABC PCN taking a GP list size of 89,814. The 1% would be 898.14 people in the last 12 months of life. Of this number 11% would be expected to be sudden death and therefore 799 people would benefit from planned palliative and end of life care.

The Midlands and Lancashire Commissioning Support Unit (CSU) (Midlands and Lancashire Commissioning Support Unit : The Strategy Unit, 2020) have produced information on usage of palliative and end of life care services. This model uses key data sets from these guides to model demand for specialist palliative care services. These have then been sense checked with system colleagues from palliative care, commissioning and public health. Where possible other sources have also been reviewed to triangulate the parameters selected for the model.

The critical question is to determine what percentage of those people who might benefit from palliative care require a more complex intervention, i.e. specialist palliative care. Murtagh et al (2014) compare methods of quantifying the need for palliative care concluding that this would be beneficial for a minimum of 63% of the population (pre COVID). Based on 2010 data, which was acknowledged as not necessarily a comprehensive picture, Murtagh et al (2014) estimate that between 100,000 – 242,000 people per annum receive specialist palliative care, however as some of this activity is likely to be for the same person, the level of duplication is not known. This is based on an annual number of deaths in their article of 470,000 per annum. However, they estimate that at mid-range 326,685 – 387,067 would benefit from specialist intervention. The lack of a full dataset on access to specialist palliative care services makes it difficult to be sure of what actual access is. However, given the inequalities of access it is fair to assume that there is unmet need. What form the intervention needs to be i.e. bed, home or day therapy is also not clear.

The starting point for this SPC Demand Model is based on how the system currently behaves. Parameters can then be altered to assess how services would need to grow in order to meet some of the unmet need.

This model uses 20% of those requiring palliative or end of life care (i.e. excluding sudden death) as an estimate. This is at the lower end of Murtagh et al (2014) estimate, however it is the % of people in the CSU data (Midlands and Lancashire Commissioning Support Unit : The Strategy Unit, 2020) of those dying with cancer. That is not to say that everyone with cancer requires specialist palliative care OR that some people without cancer do, however as a proxy measure it is a reasonable starting point. It accepts the ongoing dominance of cancer care provided by hospices which influences the number of people supported by hospices. The model can be modified for different approaches. In discussing this starting percentage with a number of healthcare colleagues, it was agreed that 20% was a reasonable starting position.

For ABC PCN of the 799 people needing planned palliative and end of life care, using the 20% proxy this would equate to 160 people requiring specialist palliative care.

The next question is of that 160 people, what type of specialist palliative care are they likely to access, i.e. a bed, community nursing and/or hospice at home?

Based on the CSU reports (Midlands and Lancashire Commissioning Support Unit : The Strategy Unit, 2020), 23% of people who die with cancer in Birmingham or 22% in Staffordshire do so in a hospice inpatient unit and 29% in Birmingham or 30% in Staffordshire die at home. These figures are used in the model recognising that in reality the percentage population will comprise of a combination of people with cancer and other diseases. Future modelling of what percentage of different disease groups require specialist palliative care would add further sensitivity to the model.

Community Nursing

To work out the proportion of the population requiring a specialist palliative nurse in the home: the figure takes the number of people requiring specialist palliative care and assumes (based on local data) that 90% would be referred to the hospice, the other 10% being an acute admission without a discharge home. There is currently no knowledge of national dataset that provides a more accurate assessment. That 90% figure becomes the number of people that would need to be accommodated by a Specialist Palliative Community Nursing team. Taking an average caseload per WTE of 30, calculates the workforce requirements and therefore enables a costed model of care. To illustrate this in practice:

For ABC PCN it would be anticipated that of the 160 people requiring specialist palliative care, 144 people would be on the case load of a specialist community team. With a caseload of 30 per whole time equivalent this would mean a team of 4.8WTE nurses would be required.

Beds

The model differentiates between two types of admission 1) an admission during which the patient dies and 2) an admission where the patient is discharged home – most likely a stay for symptom management.

The first category uses CSU data which suggests 23% of this cohort die in a hospice bed. The model uses average length of stay which can be amended for local scenarios. Pre-COVID an average length of stay would be 14 days, during the height of the pandemic this dropped significantly, however it is expected to level out at 12.

For ABC PCN of the 160 people requiring specialist palliative care, 23% would be anticipated to die in a hospice bed, i.e. having an inpatient stay that ends with their death, this would equate to 37 people. Based on an average length of stay of 12 days, this would mean that there would need to be 444 bed days to facilitate this number of people.

Hospices also offer inpatient stays for symptom management where the patient would return home. This figure is particularly challenging as there is no data set to draw from. Whilst not statistically valid, 4 hospices were asked to review the files of a random sample of 20 patients on the community case load, on average 20% of this group required a symptom management admission. Further analysis of this data set is required.

For ABC PCN their community caseload is 144, of this 29 people are likely to need an admission for symptom management. Length of stay is 12 days, therefore 348 bed days are required by this PCN.

Adding the bed days together in this example 444 plus 348 equals 792, divided by 365 would suggest this PCN would be using on average 2 beds on a rolling basis.

Hospice at Home

The model assumes that for each person who achieves a home death based on CSU data, will be supported by Hospice at Home. For this area that is 29% of people with cancer (being used as a proxy) die at home. In this example Hospice at Home is a healthcare assistant delivered service supporting someone in the last two weeks of life. A better description is that along with the specialist community team the combination of those two services provide a virtual ward for an average length of stay for 14 days. The average input calculated is 30 hours of care per person. This figure might also include some night sits and/or double up visits.

ABC PCN’s of the 160 people requiring specialist palliative care, 29% would be expected to die at home that equates to 46 people in any 12 month period. Based on 30 hours per person a total of 1,380 hours of care would be required, delivered based on individual need. Again this can then be worked through into a workforce model and costed accordingly.

Planning for increased demand

Based on Murtagh et al’s (2014) analysis, it is clear that there continues to be unmet need when it comes to access to specialist palliative care. In addition, the metrics used are of course pre COVID and do not reflect the significant challenges hospices are facing due to the number of people diagnosed late or who have had treatment delayed. Applying the analysis from Murtagh et al (2014) article it could be assumed that between 51%-82% of people dying might benefit from specialist palliative care (pre-COVID). If 51% was applied to ABC PCN, this would mean that 408 people would need to be supported rather than 160. This is a significant increase, however with potential opportunities for systems to reduce the number of people with unmet need for specialist palliative care accessing acute services.

A more immediate assessment would be modelling the increased number of deaths as a consequence of COVID. Recent analysis suggests that the 25% increase in people dying anticipated in 2040 is with us now (Cicely Saunders Institute, 2021). Using this figure on the 1% of the population being in the last 12 months of life, would create an increase for ABC PCN to 200 from 160. Another report (Maringe et al, 2020) focuses on the increase specifically for people with a malignant disease: applying an average of 7% across the groups studied and applying this to the model would increase demand for specialist palliative care to 216 from the baseline 160 for ABC PCN.

Any of the calculations in the model can be amended to support scenario planning and aspirations for improved access. For example, if a system wants to increase the number of people dying at home or dying in a hospice, the percentages from the CSU report can be altered to a more aspirational state. In doing so, the workforce and financial modelling can support commissioners in the resources required.

Limitations

There are some limiting factors in this model:-

The use of a proxy for specialist palliative care – further development of the datasets used by the CSU will hopefully enable a better metric.
There isn’t yet data on how many people with a specialist palliative care need require an admission for symptom management.
% of people known to the specialist community nursing team – an accurate metric is not available regionally or nationally.
It does not model for input into generalist palliative care for those hospices who do so.

Conclusion

There does not appear to be a modelling tool for specialist palliative care demand. As hospices need to be better at quantifying their contribution to health systems it is no longer enough to use broad metrics or financial models based on historical ways of working.

As long as the model is used as part of a system understanding and other datasets are taken into account it is useful in contributing a method of calculating demand for specialist palliative care services and is customisable enabling different value sets to be utilised.

This modelling tool is a starting point rather than a finished, polished, fully evidence-based solution.

For further information regarding the tool please contact emma.hodges@stgileshospice.com

References

Association for Palliative Medicine, 2012. Commissioning Guidance for Specialist Palliative Care, Southampton: Association of Palliative Medicine.

Cicely Saunders Institute, 2021. Action Plan for Palliative Care. [Online] Available at: https://cicelysaundersinternational.org/action-plan-for-palliative-care/
[Accessed 2nd March 2021].

Dying Matters, n.d. Identifying End of Life Patients. [Online] Available at: https://www.dyingmatters.org/gp_page/identifying-end-life-patients
[Accessed 2nd March 2021].

Help the Hospices, 2013. Future ambitions for hospice care : our mission and our opportunity, London: Hospice UK.

Hospice UK, 2015. Hospice Enabled Dementia Care: The First Steps, London: Hospice UK.

Hospice UK, 2017 Briefing : Open up hospice care, London: Hospice UK

Leadbeater, C. & Garber, J., 2010. Dying for Change, London: DEMOS.

Maringe, C., et al., 2020. The impact of the COVID-19 pandemic on cancer deaths due to delays in diagnosis in England, UK: a national, population-based, modelling study. The Lancet, 21(8), pp. 1023-1034.

Murtagh, et al., 2014. How many people need palliative care? A study developing and comparing methods for population based estimates. Palliative Medicine, 28(1), pp. 49-58.

Pooler, J., Yates, A. & Ellison, S., 2007. Caring for patients dying at home from heart failure: a new way of working. International Journal of Palliative Nursing, 13(6), pp. 266-271.

Russell, S., 2015. Do definitions matter in palliative care?. International Journal of Palliative Nursing , 21(4), pp. 160-161.

Selman, L. et al., 2007. Modelling services to meet the palliative care needs of chronic heart failure patients and their families. Palliative Medicine, Volume 21, pp. 385-390.

The Strategy Unit, Midlands and Lancashire Commissioning Unit, 2018. Patterns and Projections of Deaths in Staffordshire, Birmingham: The Strategy Unit

The Strategy Unit, Midlands and Lancashire Commissioning Support Unit, 2020. Health Service Use in the Last Two Years of Life, Birmingham: The Strategy Unit.

Tobin, J., Rogers, A., Winterburn, I. & Tullie, S., 2021. Hospice care access inequalities: a systematic review and narrative synthesis. BMJ Supportive and Palliative Care, Issue Open Access.