Trends in and drivers of Healthcare Expenditure in the English NHS : a retrospective analysis

Background: In England, rises in healthcare expenditure consistently outpace growth in both GDP and total public expenditure. To ensure the National Health Service (NHS) remains financially sustainable, relevant data on healthcare expenditure are needed to inform decisions about which services should be delivered, by whom and in which settings. Methods: We analyse routine data on NHS expenditure in England over 9 years (2008/09 to 2016/17). To quantify the relative contribution of the different care settings to overall healthcare expenditure, we analyse trends in 14 healthcare settings under three broad categories: Hospital Based Care (HBC), Diagnostics and Therapeutics (D&T) and Community Care (CC). We exclude primary care and community mental health services settings due to a lack of consistent data. We employ a set of indices to aggregate diverse outputs and to disentangle growth in healthcare expenditure that is driven by activity from that due to cost pressures. We identify potential drivers of the observed trends from published studies. Results: Over the 9-year study period, combined NHS expenditure on HBC, D&T and CC rose by 50.2%. Expenditure on HBC rose by 54.1%, corresponding to increases in both activity (29.2%) and cost (15.7%). Rises in expenditure in inpatient (38.5%), outpatient (57.2%), and A&E (59.5%) settings were driven predominately by higher activity. Emergency admissions rose for both short-stay (45.6%) and long-stay cases (26.2%). There was a switch away from inpatient elective care (which fell by 5.1%) and towards day case care (34.8% rise), likely reflecting financial incentives for same-day discharges. Growth in expenditure on D&T (155.2%) was driven by rises in the volume of high cost drugs (270.5%) and chemotherapy (110.2%). Community prescribing grew by 45.2%, with costs falling by 24.4%. Evidence on the relationship between new technologies and healthcare expenditure is mixed, but the fall in drug costs could reflect low generic prices, and the use of health technology assessment or commercial arrangements to inform pricing of new medicines

The relationship between social care resources and healthcare utilisation by older people in England : an exploratory investigation

Background Since 2010, adult social care spending has fallen significantly in real terms whilst demand has risen. Reductions in local authority (LA) budgets are expected to have had spill over effects on the demand for healthcare in the English NHS. Motivation If older people, including those with dementia, have unmet needs for social care, their use of healthcare may increase. Methods We assembled a panel dataset of 150 LAs, aggregating individual-level data where appropriate. We tested the impact of changes in LA social care resources, which was measured in two ways: expenditure and workforce. The effects on people aged 65+ were assessed on five outcomes. 1. Rates of emergency hospital admissions for falls in people with dementia aged 65 and over. 2. Rates of emergency hospital admissions for fractured neck of femur in people 65 and over. 3. Extended length of stay in people with dementia, 7 days and over 4. Extended length of stay in people with dementia, 21 days and over 5. Rates of NHS Continuing Healthcare (NHS CHC) Outcomes (utilisation) data were derived from the Hospital Episode Statistics (1, 2, 3 and 4), the Public Health Outcomes Framework (2), and publicly available datasets from NHS Digital (5). Datasets varied in the timeframes available for analysis. Planned analysis of the effects of social care cuts on delayed transfers of care in mental health trusts, and on deprivation of liberty safeguards were not undertaken because of data quality concerns. We tested the effect of two separate explanatory variables: adult social care gross current expenditure (per capita 65 and over) adjusted by area cost; and adult social care workforce staff (per capita 18 and over). Workforce measures distinguished LA and independent sector employees and included professional and non-professional staff providing direct social care. We ran negative binomial models and linear models, and controlled for a range of confounding factors, including deprivation, ethnicity, age, unpaid care, LA class and year effects. To account for potential endogeneity (‘reverse causality’), we also tested the Area Cost Adjustment (ACA) as an instrumental variable and ran dynamic panel models. Sensitivity analysis explored the effects of the additional effects of the Better Care Fund. Results The level of social care expenditure on older people was not significantly related to emergency admission rates for falls in people with dementia or for fractured neck of femur. Extended stays of 7 days or longer were significantly and positively related to the level of social care spend, but this association was no longer significant when additional spend from the Better Care Fund was taken into account. There was no significant relationship between the level of social care spend and hospital stays of 21 days or longer or between spend and uptake of NHS CHC. We also tested the effect of four social care workforce measures. LAs employing higher rates of social care staff (especially professional staff) had significantly higher levels of NHS CHC, but there was no significant relationship between LA staffing levels and the remaining four outcomes. LAs with higher levels of independent social care staffing had significantly lower rates of extended stays, but there was no association with either emergency admissions or on NHS CHC. The effect of ‘full time’ ii CHE Research Paper 174 unpaid care on outcomes was mixed, with tentative evidence of a protective effect on admissions for falls, and on extended stays of 21 days or longer. When the Area Cost Adjustment was used as an instrument in place of expenditure, results were largely consistent with the main analysis: there were negative effects on NHS CHC but no effect on any other outcome. The dynamic panel models found a positive relationship between spend and emergency admissions for falls, but the effect on other outcomes was statistically insignificant. Conclusions The study found no consistent evidence that reductions in social care budgets led to the expected rises in hospital admissions, hospital stays or uptake of NHS CHC. However, findings suggest that public sector staff providing direct social care, particularly professional staff, may be instrumental in facilitating access to NHS CHC. In addition, the study found tentative evidence that extended hospital stays are partially offset by social care provision by the independent sector and by unpaid carers providing intensive care. To test the validity and robustness of these findings, future research using linked individual-level health and social care data is needed

Approaches to projecting future healthcare demand

Background: Existing projections of healthcare expenditure in the UK describe a wide range of possible spending futures. In part, these reflect uncertainties about growth in demand, but they also reflect differences in modelling approaches and in their underlying assumptions. The rise in healthcare demand, and its consequent impact on expenditures, has stimulated interest among policymakers in better projecting future healthcare needs to aid the management and organisation of healthcare resources. More accurate projections are expected to allow the healthcare system to adapt and prepare for future challenges. However, with a plethora of different and emerging methodologies and approaches to project future outcomes and events, it is increasingly challenging to select appropriate techniques for a given research objective such as the demand for health care, within a specific context such as the UK National Health Service (NHS). Objectives: This work provides a review and critique of four approaches to projection modelling: macro-level modelling, macrosimulation, microsimulation, and machine learning. Our critique assesses these different techniques in terms of appropriateness depending on the projection objective (e.g. the impact of policy changes, drivers of demand, expenditure projection), their development and implementation costs (data requirements, maintenance, development, and running times), predictive accuracy and model fit, ease of use (implementation and interpretation), transparency, and capacity for future updates when required. Discussion: Each of the four modelling techniques has both strengths and limitations. For any given scenario, the choice among the techniques depends on the relative importance and weight placed on the particular objective, data requirements, and on the time horizon for the projection. For example, if the research objective is the long-term forecast of healthcare demand and expenditure, machine learning and macro-level models are likely to provide the most accurate models. However, if the objective is to focus on the impact of policy changes and policy scenarios, macrosimulation or microsimulation models are more suitable. The choice of time horizon of the projection, even for longterm projections, is particularly crucial, since the forecast error in the factors explaining the growth of healthcare demand and expenditure will grow as the time horizon increases

Need, demand, supply in health care : working definitions, and their implications for defining access

Effective policymaking in healthcare systems begins with a clear typology of the terminology – need, demand, supply and access to care – and their interrelationships. However, the terms are contested and their meaning is rarely stated explicitly. This paper offers working definitions of need, demand, and supply. We draw on the international literature and use a Venn diagram to explain the terms. We then define access to care, reviewing alternative and competing definitions from the literature. We conclude by discussing potential applications of our conceptual framework to help to understand the interrelationships and trade-offs between need, demand, supply and access in health care

Investigating the relationship between social care supply and healthcare utilisation by older people in England

Since 2010, adult social care spending in England has fallen significantly in real terms whilst demand has risen. Reductions in social care supply may also have impacted demand for NHS services, particularly for those whose care is provided at the interface of the health and care systems. We analysed a panel dataset of 150 local authorities (councils) to test potential impacts on hospital utilisation by people aged 65 and over: emergency admission rates for falls and hip fractures (‘front-door’ measures); and extended stays of 7 days or longer; and 21 days or longer (‘back-door’ measures). Changes in social care supply were assessed in two ways: gross current expenditure (per capita 65 and over) adjusted by local labour costs; and social care workforce (per capita 18 and over). We ran negative binomial models, controlling for deprivation, ethnicity, age, unpaid care, council class and year effects. To account for potential endogeneity, we ran instrumental variable regressions and dynamic panel models. Sensitivity analysis explored potential effects of funding for integrated care (the Better Care Fund). There was no consistent evidence that councils with higher per capita spend or higher social care staffing rates had lower hospital admission rates or shorter hospital stays

Impact of prevention in primary care on costs in primary and secondary care for people with serious mental illness

A largely unexplored part of the financial incentive for physicians to participate in preventive care is the degree to which they are the residual claimant from any resulting cost savings. We examine the impact of two preventive activities for people with serious mental illness (care plans and annual reviews of physical health) by English primary care practices on costs in these practices and in secondary care. Using panel two-part models to analyze patient-level data linked across primary and secondary care, we find that these preventive activities in the previous year are associated with cost reductions in the current quarter both in primary and secondary care. We estimate that there are large beneficial externalities for which the primary care physician is not the residual claimant: the cost savings in secondary care are 4.7 times larger than the cost savings in primary care. These activities are incentivized in the English National Health Service but the total financial incentives for primary care physicians to participate were considerably smaller than the total cost savings produced. This suggests that changes to the design of incentives to increase the marginal reward for conducting these preventive activities among patients with serious mental illness could have further increased welfare

Measuring the overall performance of mental healthcare providers

To date there have been no attempts to construct composite measures of healthcare provider performance which reflect preferences for health and non-health benefits, as well as costs. Health and non-health benefits matter to patients, healthcare providers and the general public. We develop a novel provider performance measurement framework that combines health gain, non-health benefit, and cost and illustrate it with an application to 54 English mental health providers. We apply estimates from a discrete choice experiment eliciting the UK general population’s valuation of non-health benefits relative to health gains, to administrative and patient survey data for years 2013-2015 to calculate equivalent health benefit (eHB) for providers. We measure costs as forgone health and quantify the relative performance of providers in terms of equivalent net health benefit (eNHB): the value of the health and non-health benefits minus the forgone benefit equivalent of cost. We compare rankings of providers by eHB, eNHB, and by the rankings produced by the hospital sector regulator. We find that taking account of the non-health benefits in the eNHB measure makes a substantial difference to the evaluation of provider performance. Our study demonstrates that the provider performance evaluation space can be extended beyond measures of health gain and cost, and that this matters for comparison of providers

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Live well, die well – an international cohort study on experiences, concerns and preferences of patients in the last phase of life: the research protocol of the iLIVE study

Introduction Adequately addressing the needs of patients at the end of life and their relatives is pivotal in preventing unnecessary suffering and optimising their quality of life. The purpose of the iLIVE study is to contribute to high-quality personalised care at the end of life in different countries and cultures, by investigating the experiences, concerns, preferences and use of care of terminally ill patients and their families. Methods and analysis The iLIVE study is an international cohort study in which patients with an estimated life expectancy of 6 months or less are followed up until they die. In total, 2200 patients will be included in 11 countries, that is, 200 per country. In addition, one relative per patient is invited to participate. All participants will be asked to fill in a questionnaire, at baseline and after 4 weeks. If a patient dies within 6 months of follow-up, the relative will be asked to fill in a post-bereavement questionnaire. Healthcare use in the last week of life will be evaluated as well; healthcare staff who attended the patient will be asked to fill in a brief questionnaire to evaluate the care that was provided. Qualitative interviews will be conducted with patients, relatives and healthcare professionals in all countries to gain more in-depth insights. Ethics and dissemination The cohort study has been approved by ethics committees and the institutional review boards (IRBs) of participating institutes in all countries. Results will be disseminated through the project website, publications in scientific journals and at conferences. Within the project, there will be a working group focusing on enhancing the engagement of the community at large with the reality of death and dying. Trial registration number NCT04271085

The LifeCycle Project-EU Child Cohort Network : a federated analysis infrastructure and harmonized data of more than 250,000 children and parents

Early life is an important window of opportunity to improve health across the full lifecycle. An accumulating body of evidence suggests that exposure to adverse stressors during early life leads to developmental adaptations, which subsequently affect disease risk in later life. Also, geographical, socio-economic, and ethnic differences are related to health inequalities from early life onwards. To address these important public health challenges, many European pregnancy and childhood cohorts have been established over the last 30 years. The enormous wealth of data of these cohorts has led to important new biological insights and important impact for health from early life onwards. The impact of these cohorts and their data could be further increased by combining data from different cohorts. Combining data will lead to the possibility of identifying smaller effect estimates, and the opportunity to better identify risk groups and risk factors leading to disease across the lifecycle across countries. Also, it enables research on better causal understanding and modelling of life course health trajectories. The EU Child Cohort Network, established by the Horizon2020-funded LifeCycle Project, brings together nineteen pregnancy and childhood cohorts, together including more than 250,000 children and their parents. A large set of variables has been harmonised and standardized across these cohorts. The harmonized data are kept within each institution and can be accessed by external researchers through a shared federated data analysis platform using the R-based platform DataSHIELD, which takes relevant national and international data regulations into account. The EU Child Cohort Network has an open character. All protocols for data harmonization and setting up the data analysis platform are available online. The EU Child Cohort Network creates great opportunities for researchers to use data from different cohorts, during and beyond the LifeCycle Project duration. It also provides a novel model for collaborative research in large research infrastructures with individual-level data. The LifeCycle Project will translate results from research using the EU Child Cohort Network into recommendations for targeted prevention strategies to improve health trajectories for current and future generations by optimizing their earliest phases of life.Peer reviewe