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Multiple long-term conditions - Studies within a project (SWAP)


Published: 26 May 2021

Version: 1.2 (March 2023)

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Research into multiple long-term conditions is a strategic priority for the NIHR. The NIHR has published a strategic framework for research into multiple long-term conditions (MLTC), which sets out what we mean when we talk about MLTC; our initial evidence aims to enhance the evidence base in this area; and cultural changes taking place to foster new research.
The Health and Social Care Delivery Research (HSDR), Health Technology Assessment (HTA) and Public Health Research (PHR) Programmes would like to encourage all researchers to consider an MLTC perspective in their projects and produce learning with a clear pathway to patient benefit either through the NHS, social care or public health systems or for policymakers in national or local Government; or considers the conduct and ways of delivering projects on multiple long-term conditions. This is to further understanding on MLTC and improve knowledge on the best methods and processes for incorporating MLTC research questions into complex projects (including clinical trials) in health, social care and public health. The programmes want to fund Studies within a Project (SWAPs) grounded in the complexity of research that is required to better understand MLTC, and reach the widest base and range of participants who are representative of the MLTC communities which will benefit from the findings of the research funded.

This opportunity is complementary to that for clinical trials in the HTA programme but goes broader to include research questions to incorporate an MLTC lens into funded research in addition to methodological knowledge. It is specifically related to multiple long-term conditions. The opportunity is available for all research applications to the NIHR Health Technology AssessmentPublic Health Research and Health and Social Care Delivery Research Programmes.

Examples of the type of SWAP which might be applicable to the individual programmes covered by this opportunity are listed at the end of this document. For all three programmes, examples of a SWAP could be:

  • Developing social care related outcome measures or learning on recruitment from social care settings as a high proportion of social care users will have MLTC and this will ensure research is addressing the needs of the whole person
  • Bringing a new dimension to PPIE work to consider the lived experience of people with MLTC and carers
  • Scoping how the interventions studied might be applied to populations with MLTC
  • Additional work to understand how researchers can effectively engage with people with MLTC and carers to promote the uptake and use of the evidence generated
  • Additional data collection or secondary analysis of collected data to answer questions related to MLTC
  • Methodological work on outcomes relevant to multiple conditions, including treatment burden and continuity of care
  • Learning and advances in data linkage across settings and datasets
  • Methodological work on coding, data quality and completeness for complex and multiple conditions
  • Methodological work focussing on different participant groups; how best to ensure there is a full range of participants and what tailored approaches might be needed for recruitment and follow-up in the context of the overarching project design, including outside of NHS settings
  • Work to consider training and skills needed for the health, social care, and public health workforce

Applicants can propose an embedded study within a project (SWAP) which would support the above ambition of the programmes. The study would be short and efficient, with findings put into the public domain as soon as they are available, as an interim output. The possibility of registering a SWAP is still being explored, and successful applicants will be advised when and if registration is available. A SWAP will be a small part of the overall application and should not be costed at no more than £30,000 to include all dissemination and publication associated with the SWAP.

At stage 1 applicants should indicate if they intend to include a SWAP should their application be shortlisted. Details of the SWAP are not required.

In a stage 2 application the following elements should be set out very clearly:

  • There is a gap in knowledge which the proposed SWAP would address. This might be because the methods or study design are novel or build on relatively new ways of delivering the project.
  • The context of the project warrants a SWAP: For example the complexity of the context, setting, the community the project is trying to reach, the type of population intervention is such that a SWAP might further understanding as to how best to tailor that intervention
  • The learning from a SWAP will be generalisable to other projects
  • The learning from the proposed SWAP will be immediately applicable to other projects even if they are conducted in a different setting
  • The proposed SWAP builds on existing knowledge

Programme-specific examples

(this is not an exhaustive list)


This activity could take different forms and is likely to be an enhancement of existing features of the study.  This might include (but not be limited to):

  • Additional focus on workforce roles and training for person-centred care, including generalist models
  • Additional focus on elements of case management or coordination of care
  • Additional focus on social care needs and support for people with multiple long-term conditions
  • Further analysis and qualitative work with particular sub-groups and communities of interest
  • Consideration of implementation pathways specific to MLTC
  • Testing engagement activities and tailored outputs of actionable findings for particular audiences, such as mental health, social care, or community staff; how best to achieve furthest reach, for example


This opportunity relates to study designs which are not covered by the HTA SWAT initiative. Examples of what might be appropriate for this opportunity include:

  • Different ways of ensuring outcomes are relevant to people with multiple long-term conditions
  • Different ways of embedding dissemination and uptake of research outputs by people with MLTC from all communities
  • Data linkage methods which are relevant to eliciting learning to address the needs of people with multiple long-term conditions
  • Study processes which allow for better data collection and analysis to cover people with multiple long-term conditions
  • Additional data analysis to generate findings specific to people with MLTC


The PHR Programme aims to take a population level approach in the research it funds, along with a particular focus on health inequalities. Individuals with multiple long-term conditions will often have risk factors that are associated with deprivation and other drivers of health. Given that individual risk factors and wider determinants vary significantly across different socio-economic groups, it is inevitable that the prevalence of multiple long-term conditions will also be highly variable. The programme is interested in populations with a high prevalence of multiple long-term conditions, how those conditions can be prevented, how the health and quality of life impacts can be mitigated, and how health inequalities can be addressed in this context. Given likely data deficiencies, there is scope for innovative modelling approaches that enable the impact of different interventions to be assessed.

Within the context of a PHR project on multiple long-term conditions, a SWAP could examine areas such as:

  • Methods for measuring the representation of those with multiple long-term conditions in the study population(s) and how this can be ensured to be appropriate to levels of prevalence of multiple long-term conditions in that population and maintained throughout the study
  • The impact of high prevalence of multiple long-term conditions on the study population’s ability to engage with the study, and how such impact could be mitigated.
  • Sourcing different datasets and assessing the scope for record linkage, making recommendations on what data are needed as well as what currently exist.