Published: 10 January 2023
Version: 1.0 January 2023Print this document
Timetable and Budget
|Deadline for Stage 1 applications||14 February 2023, 1pm|
|Notification of outcome of Stage 1 application||April 2023|
|Deadline for Stage 2 application||06 June 2023, 1pm|
|Notification of outcome of Stage 2 application||October - November 2023|
|Project start||November 2023|
|Project duration||24 months|
The National Institute for Health and Care Research (NIHR) Policy Research Programme (PRP) invites applications for a single research project to examine how the extreme health inequalities experienced by those in health inclusion groups impact on headline figures for mortality and morbidity at the population level.
‘Inclusion health’ describes action to improve health and care for people who are socially excluded, experience multiple overlapping risk factors for poor health (such as poverty, violence and complex trauma) and stigma and discrimination. People in inclusion health groups are not consistently accounted for in electronic health databases, which makes them effectively ‘invisible’ in health and care needs assessments. These experiences frequently lead to barriers in access to healthcare and extremely poor health outcomes, contributing considerably to health disparities.
Inclusion health groups typically include people experiencing homelessness, including people who sleep rough, vulnerable migrants, Gypsy, Roma, and Traveller communities and sex workers, as well as victims of modern slavery, people with drug and alcohol dependency and people in touch with the criminal justice system.
Hard Edges report cites that an estimated 1.8% of the population in England has at least 1 of the following: homelessness, offending and substance misuse.
While health outcomes among the general population are distributed across a social gradient, inclusion health groups instead experience a ‘cliff-edge’ effect at the margins of this gradient. For example, a systematic review and meta-analysis found that all-cause mortality in high-income countries was approximately 12 times higher in women in inclusion health groups compared with the general population, and 8 times higher in men. A similar pattern was found for morbidity in England, where one cross-sectional study in London and Birmingham found that chronic obstructive pulmonary disease prevalence was 1% and 2% for housed individuals in the least and most deprived quintiles respectively, but 14% in people experiencing homelessness.
There are a number of policy initiatives that recognise the importance of inclusion health. For example, the Department for Levelling Up, Housing and Communities (DLUHC) announced their ambitious Rough Sleeping Strategy that aims to end rough sleeping by 2024. Health plays a vital role in achieving this objective. NICE recently published its guideline ‘Integrated health and social care for people experiencing homelessness’ with recommendations to improve access to and engagement with health and social care services for people experiencing homelessness. Statutory guidance on the preparation of integrated care strategies published in July 2022 specifically acknowledges the importance of inclusion health, encouraging integrated care partnerships to include a focus on these population groups in the development of their strategies. The Department of Health and Social Care Outcome Delivery Plan: 2021 to 2022 focusses on levelling up - which includes reducing health disparities, is also a key department and wider governmental priority which this proposal can contribute to.
However, health disparities patterned by inclusion health characteristics such as migration status and homelessness do not fall under the protected characteristics outlined in the Equality Act 2010 and public sector duty. Therefore, despite mounting evidence of the striking health inequalities experienced by inclusion health groups, population health initiatives concerning inclusion health groups are often perceived as an ‘add-on’ rather than a core part of policies to address health inequalities.
Despite the stark statistics juxtaposing inclusion health outcomes with that of the rest of the population, the relatively small size of inclusion health groups means that it is still difficult to make a strong economic case for increased government spending. In other words, it is challenging to justify tackling the disproportionate burden of ill health in inclusion health groups without demonstrating how this will result in improving the statistics pertaining to the wider population's health.
One of OHID’s core priorities is to increase healthy life expectancy by 5 years. Investigating how the health of socially excluded populations contribute to broader metrics like mortality and life expectancy is a key part of understanding how this population health target can be achieved. Understanding how the broader whole-of-population health metrics are impacted by the extreme health inequalities experienced by inclusion health groups could help reframe how health inclusion should be positioned in public health policy on health inequalities.
This project therefore aims to answer the following research questions: a) What proportion of cause-specific deaths in the general population in England at specific ages are attributable to inclusion health groups? b) What proportion of morbidity outcomes (e.g., disease prevalence, avoidable hospitalisation, COVID-19 backlogs) in the general population in England at specific ages are attributable to inclusion health groups?
The project should be divided into at least two phases, with the first focusing on an assessment of possible data sources, linkages and methods for identifying inclusion health groups. Phase two will then assess cause-specific and age-specific mortality and morbidity rates in inclusion health group(s) and the general population (calculated separately), followed by robust analysis of the mortality and morbidity attributable to inclusion health groups (e.g. modelling, population attributable fractions).
Choice of inclusion health group will likely be based on availability of data and feasibility of identifying groups/multiple overlapping risk factors for social exclusion. Estimation of the size of inclusion groups and/or the extent of overlapping risk factors for social exclusion in England is an important secondary research question that this project could also answer, which will be extremely beneficial to future analyses and health monitoring projects internal and external to OHID.
The outputs generated from this project could be used to achieve alignment between priorities for inclusion health and broader cross-government priorities for population health (e.g., reducing burden of CVD and mental health).
Depending on what information is acquired, the outputs from this project could be used to undertake further cost analysis and (if appropriate) estimate how much money could be saved by addressing social exclusion in the broader context of interventions to reduce cause-specific morbidity and mortality. Outputs could support arguments to the Treasury in Spending Review bids and support internal budget and resource prioritisation within the department.
The project will identify focal points where policy development and implementation has the potential to achieve the greatest magnitude of population health benefit, i.e. assisting policy and public health delivery teams to identify and delve deeper into existing interventions/pilots for specific health outcomes that have the potential for significant scalability and impact.
Strong experience in epidemiology and quantitative analysis, including complex statistical analysis and modelling
A track record of working with routine administrative data, including data linkage.
Ability to co-design research with relevant stakeholders including those with lived experience of homelessness.
Familiarity with methods to calculate and model metrics like life expectancy, healthy life expectancy, cause-specific mortality, and avoidable hospitalisation, including in exceptional circumstances (for example, in the context of extremely disadvantaged groups).
Subject matter expertise on inclusion health is essential including an in-depth knowledge of the complex needs and barriers faced by inclusion health populations. An understanding that inclusion health populations encounter or perceive stigma, discrimination and poor representation in routine administrative data.
Experience with appropriate framing of research findings concerning inclusion health groups to mitigate further risk of stigmatisation and marginalisation.
Evidence of how previous work has impacted policy and service development, and what role they played in enabling impact.
As a product of phase 1 of the project (focussing on an assessment of possible data sources, linkages and methods for identifying inclusion health groups) an interim feasibility report should be completed within 12 months.
Project outputs from phase two will then include cause-specific and age-specific mortality and morbidity rates in inclusion health group(s) and the general population (calculated separately), followed by robust analysis of the mortality and morbidity attributable to inclusion health groups (e.g. modelling, population attributable fractions).
Selection of health outcomes should ideally be guided by a combination of government priorities, CORE20PLUS5 conditions, gap analysis of conditions for which there is less empirical evidence for inclusion health groups, and data quality and feasibility.
As referenced in section 11, the estimation of the size of inclusion groups and/or the extent of overlapping risk factors for social exclusion in England is an important secondary research question that this project could also answer.
Applicants are asked to consider the timing and nature of deliverables in their proposals. Policymakers will need research evidence to meet key policy decisions and timescales, so resources need to be flexible to meet these needs. A meeting to discuss policy needs with DHSC officials will be convened as a matter of priority following contracting.
Budget and duration
The research is expected to be delivered within a cost of £400,000 over the period of 24 months, commencing within 2 months of award notification.
The interim report is expected to be delivered within 12 months of the project commencing.
Costings can include up to 100% full economic costing (FEC) but should exclude output VAT. Applicants are advised that value for money is one of the key criteria that peer reviewers and commissioning panel members will assess applications against.
A research advisory group including, but not limited to, representatives of DHSC, other stakeholders, and the successful applicants for the research should be established. The advisory group will provide guidance, meeting regularly over the lifetime of the research. The successful applicants should be prepared to review research objectives with the advisory group, and to share emerging findings on an ongoing basis. They will be expected to:
- Provide regular feedback on progress
- Produce timely reports to the advisory group
- Produce a final report for sign off
Research contractors will be expected to work with nominated officials in DHSC, its partners and the NIHR. Key documents including, for example, research protocols, research instruments, reports and publications must be provided to DHSC in draft form allowing sufficient time for review.
The feasibility of this project is likely to be challenged by issues such as data availability, options for identification of inclusion health groups, completeness and quality of recording of social exclusion exposures/indicators.
Applications should include details about whether the researchers already have/plan to gain access to suitable datasets to carry out this analysis, including existing algorithms (e.g. electronic health record phenotypes) to identify inclusion health groups in routine data, and any existing or planned linkages of datasets that would enable better identification of inclusion health groups.
Applications should also include details on the likelihood of bias introduced by their chosen methodology and ways to address this, as well as how to account for and/or interpret unusual findings that are possible artefacts of data quality.
New Guidance on Health Inequalities data collection within NIHR PRP Research:
Health Inequalities is a high priority area within the Department of Health and Social Care and the NIHR and is often present in a majority of funded projects. We are now assessing all NIHR research proposals in relation to health inequalities. We are asking applicants to identify in their application whether or not there is a health inequalities component or theme and how this research hopes to impact health inequalities. We are also asking researchers to collect relevant data, if appropriate for the research. Our goal is to collect information on health inequalities in research and data relating to the main outcome(s) of the proposed research. Please clearly identify in the research plan section whether or not your application has a health inequalities component or relevance to health inequalities and detail the core set of health inequalities breakdowns that will be reported; if none please explain why. We understand that research projects have different methodologies and focus on different populations, so please explain what data will be collected and reported for the methodology you plan to use. If a health inequalities component is not included, please explain why this does not fit within your proposed research. This should only be a few sentences.
For quantitative research we would ideally like researchers to provide one-way breakdowns of their main outcome(s) by the following equity-relevant variables: age, sex, gender, disability, region, 5 ONS Ethnic groups, and the 5 IMD quintile groups. If more detailed cross tabulations are appropriate, please include these. This table should be submitted to NIHR PRP at the end of the project. Due to data limitations, judgement calls may be necessary about which breakdowns to report and whether to merge categories to increase counts in particular cells; we ask you to make these judgement calls yourself, bearing in mind our data curation aim of enabling future evidence synthesis work in pooling results from different studies. More details and an example table can be found in Appendix A.
For qualitative research projects, this can be purely descriptive statistics giving the number of observations against the various variables.
Further details about this new request can be found in Appendix A. .
A recording of the Health Inequalities in NIHR PRP Research Q&A Event which was held on 19 September 2022 is available to view on Youtube.
References and key documents
- Bramley G, Fitzpatrick S et al. (2015). Hard Edges: Mapping Severe and Multiple Disadvantage in England [Accessed November 2022]
- Aldridge RW, Story A, Hwang SW et al. (2018). Morbidity and mortality in homeless individuals, prisoners, sex workers, and individuals with substance use disorders in high-income countries: a systematic review and meta-analysis. [Accessed November 2022]
- Lewer D, Aldridge RW, Menexes D (2019) Health-related quality of life and prevalence of six chronic diseases in homeless and housed people: a cross sectional study in London and Birmingham, England [Accessed November 2022]
- Ministry of Housing, Communities & Local Government, (2018) The rough sleeping strategy [Accessed November 2022]
- Ministry of Housing, Communities & Local Government, (2021) Government continues drive to end rough sleeping, building on success of Everyone In [Accessed November 2022]
- National Institute for Health and Care Excellence (2022) Integrated health and social care for people experiencing homelessness [Accessed November 2022]
- Department of Health and Social Care, (2022) Guidance on the preparation of integrated care strategies [Accessed November 2022]
- Department of Health and Social Care, (2021) Department of Health and Social Care Outcome Delivery Plan: 2021 to 2022 [Accessed November 2022]
- Policy Research Programme - Health Inequalities | NIHR [Accessed November 2022]
- An example of a paper – in which the methods used may be useful for researchers to consider when developing their own proposal. Tweed EJ, Leyland AH, Morrison D, Katikireddi SV. (2022). Premature mortality in people affected by co-occurring homelessness, justice involvement, opioid dependence, and psychosis: a retrospective cohort study using linked administrative data. [Accessed November 2022]
Appendix A: Further Detail on the New Guidance on Health Inequalities data collection within NIHR PRP Research
Health Inequalities is a high priority area within the Department of Health and Social Care and the NIHR and is often present in a majority of funded projects. We are now assessing all NIHR research proposals in relation to health inequalities. We are asking applicants to identify in their application whether or not there is a health inequalities component or theme and how this research hopes to impact health inequalities. We are also asking researchers to collect relevant data related to health inequalities, if appropriate for the research. Collecting specific information about health inequalities in research submitted to the programme will allow for categorisation of health inequalities research, curation of data to aid future health inequalities research and enable policymakers to better understand the implications of health inequalities within their policy areas. This is a new request from the NIHR PRP and we will be continuing to monitor queries and adapt the process as needed. If you have any feedback on this new request, please contact us at email@example.com.
Our goal is to facilitate more widespread and consistent reporting of health inequality breakdown data relating to the primary outcomes of NIHR funded research. We would ideally like researchers to focus on the following equity-relevant variables: age, sex, gender, disability, region*, 5 ONS Ethnic groups**, and the 5 IMD quintile groups. These variables are considered an ideal, but we understand that these are subject to change depending on the sample population and specific research question.
For qualitative research projects, this can be purely baseline characteristics of the participants, for example, the number of participants in each ethnic group.
For quantitative research projects, if there are multiple outcomes/effects with your stakeholders, select a small number of main outcomes as appropriate to report equity breakdowns. We will not be prescriptive about the number of the outcomes, as it will depend on the number of study design types and the nature of the project aims. We are asking for one way cross tabulations of each primary outcome by these equity-relevant variables, if appropriate for your research, together with the number of observations in each cell. If more detailed cross tabulations are appropriate for your proposed research, please include these as well. This request applies to both primary data collection studies and secondary analysis of routine data, and to causal inference studies as well as descriptive studies; however, if this is not possible due to data limitations then please explain. Due to sample size and other data limitations there may be difficult scientific and/or data security*** judgement calls to make about which breakdowns to report and whether to merge categories to increase counts in particular cells; we ask you to make these judgments yourself, bearing in mind our data curation aim of enabling future evidence synthesis work in pooling results from different studies. We also ask that researchers report breakdowns for the unadjusted as well as adjusted outcomes/effects, as appropriate.
We understand that research projects may employ different methodologies, and focus on different populations. Please explain how the variables and data collection methods chosen are appropriate to the methodologies used.
We ask that you please clearly identify in the research plan section of the application whether your application has a health inequalities component or not and detail the core set of health inequality breakdown data that will be collected, if applicable. Submission of the data collection will be a condition of the final report for all research with relevant methodologies regardless of whether the research has a health inequalities component that will need to be submitted to NIHR PRP when the grant has finished. This should only take a few sentences within the research plan section.
* Table below uses the nine regions in England, further regions can be used if using the UK as the study population. Please report region breakdown for large samples in nationally representative descriptive studies. There is no need to report this for small sample studies, for sub-national studies, or for quasi-experimental studies where it would require time-consuming re-estimation.
** White, Mixed/ Multiple ethnic groups, Asian/ Asian British, Black/ African/ Caribbean/ Black British, Other ethnic group. If the sample size is small then it is fine to report only some of the requested equity breakdowns and to merge some of the sub-groups as appropriate.
*** For guidance on how to handle data security concerns in reporting of sensitive data please see ONS guidance.
Example data table for submission at the end of the funded research project
(N.B. If there is more than one main outcome then you will require more tables and if you adjust your outcome then you will need two tables for the adjusted outcome and unadjusted outcome. For other methodologies, variable vs number of observations may be more appropriate to record participant data). This table is for an example only. It does not contain sub variables and does not illustrate any preference for certain variables, as these will be dependent on the proposed research.
|Variable||Outcome (an appropriate average for this subgroup, usually the mean)||Number of observations||Additional information about variation if appropriate, e.g. range, standard deviation|