Understanding what drives demand for health care (including the interactions with social care) and how demand may change in future is essential to inform long-term workforce and infrastructure planning. The overarching aims of this workstream are to understand the key drivers of demand and to provide projections of future demand. Research is organised within 4 Work Packages (WPs):

WP1   Conceptual / theoretical framework: Evaluations of the drivers of the demand for health care typically infer demand from expenditure and activity. However, this captures only ‘expressed’ demand. The WP will develop a conceptual framework that distinguishes the different types of demand and that informs our understanding of demand drivers.

WP2   Evidence on drivers of demand: This WP will consider evidence on the link between proxies for need and service use, and how these have changed over time. It will build on earlier ESHCRU work examining the drivers of inpatient hospital expenditures and activity. It will examine the rise in expenditures across periods and their determinants through, for example, changes in patterns of morbidity, characteristics of patients and providers. It will also consider evidence on expenditure at the end of life.

WP3 Towards a model of demand for health care: The key challenge for projective future health care demand is recognising that the system is complex, diverse and involves consideration of flows (e.g. hospital admissions) and stocks (waiting times). Potential modelling approaches may include focusing sequentially on different conditions / clinical areas. We will also consider the compatibility of a health care model with the long-term care (LTC) model, ensuring the two models can be integrated into an overall model of health care and LTC demand.

WP4 Variations in supply: This WP will consider systematic variations in the supply of health care services, setting out a conceptual framework and devising empirical strategies for identifying and quantifying variation.

PSSRU (now CPEC) has developed a number of models for producing projections of demand for long-term care and associated expenditure. The models have been used extensively for producing projections for Spending Reviews, reviews of the social care funding system and OBR fiscal sustainability analyses.

This project aims to extend the models to include (a) community health services and (b) a wider range of needs measures.

Community health services: to date, the models have mainly focused on social care. People with long-term care needs may require social care, community health care or combinations of social care and community health care. This project aims to extend the models to cover community health services (CHS), in particular community nursing and therapy services.

Need measures: the models contain as their key measure of need limitations in Activities of Daily Living (ADLs) and Instrumental Activities of Daily Living (IADLs). Since use of CHS may meet different types of needs and some evaluations of interventions have used different needs measures, we will also extend the models to include more needs variables.

The Covid-19 pandemic has changed how health care – including hospitals, prescriptions and GP appointments – is accessed and used.  This could cause both unmet need and an increased future demand for health care, which we term `displaced’ demand.  It is likely that the impact of the pandemic varies by the type of patient, their age, sex and ethnicity.  Impacts might also vary across different parts of England and depend on how much disadvantage there is.

Understanding the volume of displaced demand and how this varies across different groups is important for prioritising and managing NHS and social care spending as the impact of the pandemic subsides.  We also need to understand how much of this fall in activity is driven by ‘supply’ – availability of doctors, nurses, beds, operating theatres – and how much is due to changes to ‘demand’, e.g., by patients cancelling appointments, or failing to attend an appointment they needed. This project aims to disentangle these issues by answering the following research questions:

• How has the pandemic impacted health care use in England, and how does this vary across different groups of patients and geographies?
• What are the underlying mechanisms that led to displaced demand?
• Has social care acted as a substitute for health care?
• What are the policy implications of displaced demand in terms of prioritising what care to provide, and tackling uneven and unfair health gaps between people?

We will address these questions using both a literature review and data analysis. We will review other studies of the effects of the pandemic on health care use.  We will use hospital administrative data to track levels of inpatient and outpatient care from the start of the pandemic to the end of 2021. We will then use household survey data, such as UKHLS and ELSA, to separate out how much displaced activity was due to patients not pursuing care and/or care being cancelled, and whether social care was substituted for health care.

During the COVID-19 pandemic the number of visits to hospital A&E departments in the UK fell by up to 57%. A&E visits remained at below-normal levels for over one year until May 2021 when they began to return to normal levels. Research suggests that one of the reasons for the fall in visits was due to people’s fears of catching COVID-19 in hospital. We know that people’s risk of catching COVID-19 disease has varied throughout the pandemic in different areas of the country and has been higher at certain times than others. We also know that different types of people, eg the elderly, or those from ethnic minority groups, were more likely to suffer from severe symptoms of COVID-19. In this project we want to understand how people’s decision to attend A&E was affected by their perceptions of risk from COVID-19 and how this effect may translate into changes in A&E visits in the future.

We will analyse data from hospital A&E departments from 2020 to 2022 comparing different areas of the country and different patient groups (eg by age, gender, ethnicity, co-morbidities and deprivation). Our analysis will show if the COVID-19 pandemic contributed to inequalities in use of A&E.  For example, did people from low-income areas miss out on treatment more than those from more affluent areas. We will compare the changes in visits for different types of treatment such as mental or physical health conditions as well as urgent conditions (eg a stroke or heart attack) and non-urgent conditions (eg a mild gastrointestinal infection).

This project will help the Government design policies which will ensure people seek treatment from hospital A&E departments when they need it or access alternative sources of care or support when A&E isn’t appropriate. For example, it could shape the design of patient-facing websites and the 111 telephone service.

This project will examine the use of the Community Health Services (CHS) by different groups of patients and by geographical area. The CHS are important for the care of people living in the community with a range of health conditions that require nursing or therapy services in their own homes. They can have a valuable role in promoting independence, preventing hospital admission and expediting hospital discharge.  The project will explore how service use varies by age, gender, ethnicity and health condition (broadly defined) and also by features of the patient’s area of residence, such as its rurality (that is, if the area is rural or urban) or how disadvantaged it is.  This evidence can help policy makers to tackle health inequalities.

The project will also produce projections of demand for CHS nationally and locally for the next 10 years. It will involve analyses of linked data from the NHS Community Services Data Set (CSDS) and Hospital Episodes Statistics (HES) and the production of a simulation model to produce the projections.  The projections will reflect official populations projections on the numbers of people by age and gender and will not take account of future changes in policy or future patient preferences.

We will consult public advisers, organisations supporting patients, and commissioners and providers of CHS, as we conduct the project. The findings will provide evidence to inform national and local planning of CHS. They could inform Spending Reviews, policy development and planning of CHS at national and local level, including informing ways for the CHS to address health inequalities. We will promote the impact of our findings through offering presentations and discussions to the Department of Health and Social Care, NHS England and relevant professional and voluntary sector organisations.

This project will focus on examining use of the Community Health Services (CHS) by hospital inpatients and outpatients with health conditions for which their use is important. It will also consider the use of adult social care (ASC) by these patient groups by age and gender, drawing on findings from other studies (e.g. work conducted by the Adult Social Care Policy Research Unit – see https://www.ascru.nihr.ac.uk), so that use of CHS and ASC can be compared.

The CHS are important for the care of people living in the community with a range of health conditions that require nursing or therapy services in their own homes. They can have a valuable role in promoting independence, preventing hospital admission and expediting hospital discharge.

The project will involve analyses of linked data from the NHS Community Services Data Set (CSDS) and Hospital Episodes Statistics (HES). It will include consultation with clinical experts and policymakers about the health conditions for which use of the CHS is likely to be especially important to enable people to live in the community, prevent hospital admission and expedite hospital discharge.

We will also consult public advisers, organisations supporting patients, and commissioners and providers of CHS, as we conduct the project. The findings will provide evidence to inform policy developments relating to the CHS, especially policy developments to improve the interface between hospital and community health services. We will promote the impact of our findings through offering presentations and discussions to the Department of Health and Social Care, NHS England and relevant professional and voluntary sector organisations.

This Workstream focuses on the interdependence between health and social care (H&SC) services. The overall aims are:

To understand how variations in H&SC service provision affect the care system as a whole, for example due to demand substitutability and complementarity across services and sectors.

To understand and assess different models of service coordination, and the extent to which existing arrangements maximise potential care synergies and achieve truly integrated care.

Previous studies have aimed to identify best practice in hospital discharge arrangements. NHS England and NICE have produced recommendations on arrangements to optimise the transition from hospital to social care support. These tend to emphasise system-level processes for care coordination, such as regular management meetings, clear delineation of provider roles and responsibilities, monitoring of pressures, and pooling of resources.  At practice level, recommendations cover the establishment of joint local protocols and assessment forms, secure communication methods, up-to-date care directories, single points of access and named contacts.

In practice, the take-up of recommended discharge arrangements has been limited: for example, less than half of hospitals have developed joint or shared patient assessments. Furthermore, there is no quantitative evidence of the impact these different arrangements have on system performance. This project will contribute to the development of good practice in hospital discharge in England by:

• Mapping the range of H&SC discharge coordination arrangements in place across English hospitals.
• Engaging with H&SC stakeholders to understand which factors facilitate (or undermine) the implementation in practice of recommended discharge arrangements.
• Quantifying their impact on post-operative care costs and outcomes for different patients.

Care arrangements for coordinating H&SC services vary significantly across local areas, in terms of the nature and extent of joint funding, care models, managerial structures, and information systems. These variations are likely to influence system performance and the success of future reforms.

Our research aims to map the different H&SC coordination arrangements across England and to explore their consequences on costs and outcomes of the care economy.  We will:

• Compile evidence describing local H&SC joint working arrangements.
• Assess what types of integrated care arrangements exist, and how they respond to local characteristics.
• Quantify the impact of different integration arrangements on H&SC expenditure and system performance.

A critical question regarding the integration of the H&SC systems is the extent to which the two types of services substitute for each other, and in particular the extent to which increasing social care support reduces demand for health care. For patients admitted to hospital, greater availability of social care support should facilitate the discharge process and so reduce post-operative length of stay.

Whereas there is some evidence that this substitution effect does take place, this evidence is limited and does not differentiate between different types of patients. Increasing our understanding of these effects should provide critical evidence for optimising resource investment across acute and non-acute service areas.

Our research will aim to understand the extent to which greater supply of community and residential-based social care impacts hospital length of stay and 30-day readmission rates for older patients with different health care conditions. This project will build on analyses of the impact of complexity of discharge arrangements on lengths of stay using Hospital Episodes Statistics linked to the ESHCRU I programme of work, using panel datasets matching HES data to local authority-level data about supply of community and institutional social care.

Whereas we hypothesise a negative relationship between social care supply and hospital lengths of stay, the effect on readmission rates could be either negative (because greater social care support reduces the risk of deterioration post-discharge) or positive (because discharging earlier patients as a result of the availability of social care increases the risk of subsequent readmissions). The analysis will attempt to disentangle these effects.

Providing appropriate support for patients after they are discharged from hospital can be crucial to enabling them to leave hospital as soon as possible and to help them have the best quality of life. This study aims to understand how arrangements for discharging patients back into the community (known as Discharge to Assess or D2A) impact on the use of care services and outcomes of the health and social care system.

The study will:

• Describe how discharge services are organised in different local authorities. To do this we will a) carry out a survey of how the discharge process is arranged within these local authorities, and b) interview care professionals responsible for the discharge process.
• Collect and analyse data about the number of patients discharged from different hospitals, their characteristics and the support provided to these discharged patients.
• Understand the use of care services following discharge from hospitals, and how it affects the demand for community health and social care services.

The overall aim of the project is to identify how different ways to arrange hospital discharges affect the costs and outcomes of the care system. These results will help the development of future policy and practice advice regarding hospital discharge arrangements in England. Evidence-based improvements in policy and practice can contribute to improving the support that patients receive following their hospital discharge, to achieve better outcomes and increase efficiency in the use of the health and social care resources.

Care services often provide community-based reablement and rehabilitation services to help people with health and social care needs to regain and maintain their independence. These services are particularly important for patients discharged from hospital. Understanding how reablement and rehabilitation support is provided to people needing different types of care is therefore very important.

The project aims to:

• Summarise existing evidence about how reablement and rehabilitation services work in England.
• Understand whether it is possible to use data held by local authorities to analyse community-based reablement and rehabilitation support services.
• Understand whether there is a good supply of these services and how they are provided to people with different care needs.

To achieve these objectives, the project includes the following elements:

• Rapid review of the literature on the organisation and impact of reablement and rehabilitation services in England.
• Work with 7 local authorities to understand whether it is possible to extract linked individual-level health and social care records with information about care needs and use of reablement and rehabilitation support.
• If suitable administrative data can be found, to use statistical analysis to understand how reablement and rehabilitation services are used.
• Interview key health and social care professionals to understand challenges and opportunities for improving reablement services post-hospital discharge in England.

We will concentrate our analysis in the London region, but we are seeking to broaden the geographical coverage of the study.

We will summarise the results of the project through:

1. a note explaining the potential to extract individual-level evidence about reablement services and their potential use for analysing how the care system works
2. a report of the results of the rapid literature review and the findings from the interviews with professionals involved in the provision of community reablement and rehabilitation support
3. a report analysing the patterns of use of reablement and rehabilitation services and their association with care needs and other health and social care services.

Social care aims to improve the quality of life of service users, but it can also have wider benefits for the economy and for society. For example, by supporting people of working age, either those receiving care or their unpaid carers, social care can help these to be more productive at work or to start a paid job.  Social care may also reduce the amount of hospital services used; for example, hospital patients recovering from surgery can be moved home more quickly if supported by social care. Currently, there is very limited evidence about these wider effects of social care on the broader economy.

This project aims to address this lack of evidence by investigating how publicly funded social care services affect individuals’ net production, which is what individuals produce after taking account of what they consume, either as part of the paid economy (e.g. by being employed or by buying goods and services) or as unpaid service (e.g. by providing or receiving unpaid care). This evidence can support policy makers in their decisions about how to spend funds within the social care sector and across the public sector more broadly. Information on these wider effects provides a more complete picture of the ‘opportunity costs’ of investment decisions: the benefits that would be lost if funds were not invested in the public social care sector. For example, it can help decision makers to judge whether a new social care intervention provides value for money, which is the case if the wider benefits it offers exceed the benefits that would have been produced if the money were left invested in existing services.

Modelling risk sharing and incentive implications.  The focus of this longer term (3 year) project is on changing purchasing arrangements in the NHS and especially the movement away from purely activity-based payment (such as under the national tariff) towards mixed capitation / activity payment. One very important aspect of that change is how purchasers and providers of care will accommodate risks of activity being higher than anticipated. A second crucial aspect is the incentives that these arrangements give rise to in terms of influencing the volume, quality and cost of health care. The first elements of this project involve reviewing and applying conceptual frameworks for understanding these issues and the trade-offs that emerge (for example an incentive to better control activity but a reduced emphasis on quality of care). The conceptual frameworks imply that the benefits and costs depends on certain key parameters (such as how inherently variable volume is) and we intend to evaluate different payment mechanisms against these frameworks using data from current NHS emergency admissions.

This is an 18-month project with a specific focus on evaluating the potential benefits and risks of utilising outcome measures (specifically patient reports or PROMs) as a means of conditioning how much payment the providers of services receive. The first strand of this project is to construct a model of an idealised payment scheme based on rewarding the health gains produced from treatment. That model will in particular set out what the key parameters (things that the purchaser can observe and measure) of the idealised payment system are. The model will then be simulated based on data from one or more PROMs elective procedures. It will provide direct estimates of the bonus that might be paid by a purchaser to the providers of services.

The COVID-19 pandemic has diverted NHS resources away from planned care (such as elective hospital admissions and outpatient consultations), leading to increased waiting times.  Longer waiting times delay the health benefits from treatment, can worsen the health of those whilst waiting, reduce the ability to benefit from treatment, and increase emergency admissions and complications. They can also increase the cost of treatment, if patients become more ill while waiting.

Decisions by policymakers over funding, and the efficient and equitable allocation of resources requires knowledge of how waiting times affect health outcomes and costs.

This project will examine the impact of waiting times for hospital treatment on health outcomes, utilisation and costs for a selection of common (urgent and non-urgent) elective conditions and/procedures.  We will also investigate the health inequalities of access to planned care, mainly by analysing how the impact of waiting times varies with age, gender, ethnicity, income deprivation and location, and how the impact has changed during the COVID-19 pandemic.

The project will focus on common high-volume conditions and/procedures that affect a significant part of the population, and for which meaningful outcomes can be defined. These will include: hip and knee replacement, cardiovascular diseases (e.g. coronary heart disease of patients requiring coronary bypass or angioplasty) and/or common cancers (e.g. breast, prostate, lung) requiring urgent care, and where delayed treatment can have serious health consequences.

This research will improve knowledge and understanding of the likely impact of waiting list backlogs, by providing evidence on how waiting times affect health outcomes, utilisation and costs. This will help inform funding decisions by policymakers, in the short- and long term; and decisions as to whether reorganisations of services are required to mitigate the effect of long waiting times on patients, particularly those with a high level of need.

Looking at different patient characteristics, such as age, gender, comorbidities, ethnicity, and deprivation will enable policymakers to make decisions in the future which improve outcomes for specific groups of patients and help to reduce health inequalities.

The Covid-19 pandemic has moved NHS resources away from providing common operations, leading to increased waiting times and delaying health improvements from treatment. For a given type of operation, hospitals prioritise patients so that those who benefit most from having the operation, will get treated first. However, we don’t know much about how prioritisation is happening, nor the extent to which this should be further encouraged in the light of the current backlog.

This project will examine waiting time prioritisation for patients having hip and knee replacement operations, looking at how different types of patients experience different waiting times in the years before and during the Covid-19 pandemic. We will look at the waiting times of groups of patients who differ by factors of health need such as pre-operative health status, age, and gender; and socioeconomic factors including deprivation on income and education, and ethnicity. We will also compare how the types of patients being treated changed during the pandemic, and find out how much of the change in prioritisation is due to the change in which patients are coming forward for treatment rather than because of decisions made by hospitals.

The project will also examine the extent of waiting times inequalities for common cancers (e.g. breast, prostate, lung, bowel cancer), taking into account other patients’ characteristics, before and during the Covid pandemic.

This study will show how hospitals are choosing which patients to treat first (prioritising) and how changes in prioritisation have affected equity in access to common operations, and help the government decide which policies may further encourage prioritisation based on need and ability to benefit. Our project’s results will also identify when prioritisation is going wrong and some patients are unfairly missing out on treatment, or having it later. This will help the government to tackle health inequalities by changing or introducing policies which affect how prioritisation happens in the NHS.

The NHS in England cannot treat every patient immediately. Patients with urgent health needs will often be seen within hours. Other patients with less urgent needs often wait weeks or months before they are seen by a doctor or receive care. This includes patients waiting for surgery such as hip replacements or eye surgery.

The NHS waiting list for less urgent treatments has grown steadily since the start of the COVID-19 pandemic. There are now several million people waiting for planned surgeries. Planned surgeries are those which can be booked in advance after a patient has seen a doctor who specialises in their health condition. Some patients can expect to wait over a year before they have surgery.

Patients may become unwell when they are waiting for their surgery. This means that some patients may not be able to live a normal life while they are awaiting treatment. Their health condition may also get worse, and treatment may become less effective. But how should the NHS decide which patient groups to treat first?

In this research study we will study how waiting for planned surgery affects patients’ health. We will work out the health effects of waiting for some common forms of surgery. We will study how waiting affects how long patients can expect to live and what quality-of-life they have. We will look at this using information from clinical studies and hospital medical records. We think that the negative effects of waiting are worse for some types of surgery (e.g. heart surgery) than others (e.g. hip replacement). Our research will help NHS managers decide which waiting lists they should tackle first.

During the early months of the pandemic, English hospitals stopped routine surgery and diagnostic testing to free up space for COVID-19 patients. While care services are now getting back to normal, there are still millions of people who are waiting for the operations or diagnostic tests they need.

The NHS has introduced two new types of services to help reduce the backlog of care and reduce the time it takes for patients to be seen:

• High volume low complexity surgical hubs are small NHS hospitals that focus on a small number of planned operations and will only treat patients who are otherwise healthy. This should allow hubs to treat more patients on a daily basis.

• Community diagnostic centres will be located in city centres or other convenient locations and will provide easier and more direct access to the full range of diagnostic tests that patients may need.

Surgical hubs and diagnostic centres are not new ideas. In this study we will review previous research to find out if they are likely to work and what factors will influence how well they work and how fairly they work for different types of patients. We will use ideas from economics to describe how these new types of facilities could work. If we can access the right type of data, we also plan to analyse whether community diagnostic centres – which have been up and running for longer than surgical hubs – are helping to reduce waiting times in practice, and whether these benefits differ between patient groups.