*Important information: please note that this call is now closed and this page is retained for information purposes only.
Timetable and budget
Wave 1
| Step |
Development Awards (leading to a Research Collaboration) |
Research Collaborations |
|---|---|---|
|
Deadline for submission (stage 1) |
29 September 2020 |
29 September 2020 |
| Notification of shortlisting |
N/A |
w/c 16 November 2020 |
| Deadline for submission (stage 2) |
N/A |
9 February 2021 |
| Notification of outcomes | November 2020 |
April 2021 |
| Expected start | January 2021 |
June 2021 |
Wave 2
| Step |
Research Collaborations |
|---|---|
|
Deadline for submission (stage 2) |
05 October 2021 |
|
Notification of outcomes |
w/c 01 December 2021 |
|
Expected start |
April 2022 |
Budget and duration
| - | Development Awards | Research Collaborations (wave 1) | Research Collaborations (wave 2) |
|---|---|---|---|
| Budget | Up to £120k per project | £2.5-5m per Research Collaboration | £2.5-4m per Research Collaboration |
| Duration | 8 months | 36 months | 30 months |
Summary
1. The NIHR invites proposals to undertake programmes of research to spearhead the use of artificial intelligence (AI) methods to develop insights for the identification and subsequent prevention of multiple long-term conditions (multimorbidity) or MLTC-M.
2. Research funded through this initiative will use AI and data science methods, combined with expertise in clinical practice, applied health and care research and social science, to systematically identify or explore clusters of disease. In addition to the identification and mapping of new clusters of disease, the call seeks research to better understand the trajectories of patients with MLTC-M over time and throughout the life course, including the influence of wider determinants such as environmental, behavioural and psychosocial factors.
3. This competition aims to bring together multi-disciplinary Research Collaborations to build on our existing understanding of disease clusters in people with MLTC-M using ground-breaking AI techniques; and to grow capability for multi-disciplinary working in this crucial research area.
4. In order to facilitate new collaborations and build capability, this call has a two-stream approach. Existing groups can apply for full Research Collaboration funding, building on their strong base of multi-disciplinary researchers and bringing on board new disciplines to meet the remit of the call, as required. Awards of £2.5-5m will be available for up to 36 months for a full Research Collaboration in wave 1. Applicants who are interested in applying but need more time and resources to develop a competitive proposal, may apply for a preparatory Development Award of up to £120k for 8 months before applying for a full Research Collaboration of £2.5-4m over up to 30 months at wave 2. Development Award holders will submit their full Research Collaboration application to the Wave 2 call. We reserve the right to open the Wave 2 call to new Research Collaboration applicants. This decision will be made after the funders have reviewed the responses and funding awards made at Wave 1.
5. The NIHR will also establish a Research Support Facility for the funded Research Collaborations. The call to commission this facility will be launched shortly and the overarching aims are set out in para 36.
6. Bringing together AI specialists with experts in MLTC-M research offers an opportunity to make a significant contribution to scientific knowledge on disease clusters. This knowledge will be a fundamental step towards enabling larger-scale experimental and stratified medicine studies in the future and will provide evidence on how we might better configure the health and care system to meet the needs of people with MLTC-M.
Definitions
7. For the purpose of this document, the following definitions apply:
- Artificial Intelligence: the use of digital technology to create systems capable of performing tasks commonly thought to require ‘intelligence’.[1] AI is constantly evolving, but generally it:
- involves machines using statistics to find patterns in large amounts of data
- is capable of performing repetitive tasks with data without the need for constant human guidance
- Machine learning: is a subset of AI and refers to the development of digital systems that improve performance on a given task over time through experience
- Multiple Long-Term Conditions (Multimorbidity): The co-existence of two or more long-term conditions, each one of which is either:
- A physical non-communicable disease of long duration, such as a cardiovascular disease or cancer
- A mental health condition of long duration, such as a mood disorder or dementia
- An infectious disease of long duration, such as HIV or hepatitis C
The NIHR has published a Strategic Framework for MLTC-M Research that provides more information on how we define MLTC-M.
Background
8. A substantial and growing number of people around the world suffer from two or more long-term conditions, sometimes referred to as multimorbidity (MLTC-M). Having multiple long-term conditions affects quality of life, leads to poorer health outcomes and experiences of care, and accounts for disproportionate healthcare workload and costs. However, current understanding of how conditions co-occur or ‘cluster’, the complex interactions of different conditions and treatments and the underlying pathways throughout the life course is limited.
9. MLTC-M are particularly prevalent in older people. A large study in Scotland reported that nearly 65% of those aged 65-84 years were identified as having multiple long-term conditions, and this increased to 82% of those over 85 years.[2] However, MLTC-M affect people across the life-course so in absolute numbers, the majority of people living with MLTC-M are under the age of 65. Children with congenital conditions can have multi-system problems which accumulate in much the same way as multiple long-term conditions; and young people often have a combination of physical and mental illnesses, and the interaction between the two makes each harder to treat. In addition, certain periods of life, such as pregnancy, increases the probability that multiple conditions will present simultaneously. A life-course approach is key to better understanding of how clusters of disease co-occur.[3]
10. Research also suggests other factors are important in the development and trajectories of MLTC-M. Socioeconomic deprivation is strongly related to the acquisition of multiple long-term conditions, appearing some 10-15 years earlier in people living in the most deprived areas compared with the most affluent areas.[4] Behavioural risk factors including unhealthy diets, high levels of alcohol consumption, lack of physical activity and smoking increase the risk of disease occurring, thereby increasing the risk of MLTC-M. Evidence also suggests MLTC-M is linked to exposure to risk factors in early life[5] (e.g. environmental factors, adverse childhood experiences) and compounded by adverse events later in life. Wider determinants of population health are important for this call.
11. The development of multiple long-term conditions in an individual is often not a random assortment of diseases, but a non-random series of predictable clusters of conditions. Clusters of conditions can be due to biological, lifestyle or environmental risk factors. Some clusters of conditions are well-known (such as type 2 diabetes, heart disease and stroke), but there are others that will be identified by the application of AI and data science techniques to large scale datasets.
12. Developing a better understanding of disease clusters in MLTC-M, including trajectories over the life course, requires novel and powerful research and analytical tools that can operate across complex and distributed sets of data and sources of evidence. For example, pattern recognition can look for de novo clusters, taking an agnostic approach to discovery, paired with a deep clinical understanding to interpret the data will ensure that identified clusters are clinically meaningful.
13. Following the publication of the Academy of Medical Sciences (AMS) report Multimorbidity: a priority for global health research, and subsequent workshops, the NIHR, MRC, Wellcome and the AMS have come together to coordinate a cross-funder group to progress the research agenda in this area. The group has published a cross-funder multimorbidity research framework that aims to deliver a step-change for understanding the clusters, mechanisms and causes, prevention, management and treatment of multimorbidity through research. The NIHR has published a response to this in its Strategic Framework for Multiple Long-Term Conditions (Multimorbidity) MLTC-M Research, which sets out our high level aims for an evidence base; and a cultural change to facilitate high-quality research for patient benefit.
14. The NIHR has already made a firm commitment to funding research MLTC-M, including the identification and mapping of disease clusters, which is the first evidence aim in the NIHR Strategic Framework on MLTC. The NIHR has launched the funding calls Multimorbidity in the UK population and Tackling Multimorbidity at scale: Understanding disease clusters, determinants and biological pathways, in partnership with the MRC. We seek to build on and complement this work.
15. The NIHR is running a £140m scheme in partnership with NHS England aimed specifically at realising the potential of AI for the benefits of patients and the NHS: the Artificial Intelligence in Health and Care Award. This is part of the £250m funding for an NHS AI Lab announced by Secretary of State for Health and Social Care in August 2019.
16. The UK is making additional significant investments in the development and deployment of big data, AI infrastructure, tools and techniques, including but not limited to: investment in the Alan Turing Institute as the national institute for data science and AI; Health Data Research UK’s (HDR-UK) National Multimorbidity Resource; and the Health Foundation’s Networked Data Lab initiative. Applicants to this call should situate their proposed programme of research in the context of previous NIHR calls and these national initiatives.
17. The NIHR will work with a wide range of stakeholders to promote this significant investment, stimulate the AI and machine learning community and mobilise the expertise required to make the funded projects a success. The UK is ideally placed to capitalise on this new technology given the quality and range of data available across the health and care system.
Research priorities in MLTC-M
18. This call will specifically support the application of advanced data science and AI tools to systematically identify or further explore disease clusters in people with MLTC-M at different stages of the life course and across the life-course (e.g. exploring the trajectories and/or development of clusters of conditions over time including disease progression). To achieve the aims of this call successful Research Collaborations will need to combine technical skills and expertise in AI and data science, with clinical and health and care research expertise.
19. Research in scope for this call could include:
- Identifying and describing new disease clusters in the general population and well-defined population and patient sub-groups; exploring the trajectories of disease progression, including timing and direction of causal relationships.
- Understanding the development of and interaction between MLTC-M at different stages of the life course, including early life determinants and risk factors of defined clusters as well as biological, environmental, behavioural and social determinants of disease aetiology and progression; exploring differences related to socio-demographic characteristics and links between conditions and treatments.
20. Projects should consider the populations likely to be living with greatest burden from MLTC-M and seek to meet the knowledge and needs of groups or regions with the highest health need. Burden on the individual, whether caused by the conditions themselves, the health and social care system response, treatment or polypharmacy, or the wider socio-economic context is key.
21. The NIHR acknowledges that there are significant barriers and challenges to accessing and using relevant data about individuals using health and social care services. Applicants are expected to explain which data sources they will use in order to complete their research, to outline the benefits and suitability of using this combination of data sources and to outline the expected challenges in accessing and handling these sources.
22. Projects that focus on patients with complex MLTC-M (four or more conditions), rather than just two conditions are encouraged. In addition to cohort data, social and behavioural longitudinal studies and large-scale NHS datasets, data including endotypes are in scope to identify clusters. Precursors to disease such as obesity are also in scope. Co-morbidity to an index condition is not in scope.
Strategic objectives
23. The funding available through this call will lead to scientific understanding which will allow researchers to start addressing key challenges in the treatment and management of MLTC-M in the health and social care system in the future. We ask applicants to consider a clear pathway to implementation for the health and care system; and for drug discovery/ re-purposing and polypharmacy, appreciating that this is unlikely to be achieved within the timeframe of this call, but that future work will build on the evidence, including interim findings, with a longer term pathway to patient impact.
24. This will include:
- finding solutions for the UK health and social care sector; improving the quality of life and health outcomes for people with MLTC-M;
- exploring steps for new approaches and future industry collaborations to diagnose disease early, progress drug development and address the burden of polypharmacy; and
- to reduce progression to a greater number of conditions.
Each application should outline how the proposed knowledge and data generated will ultimately lead to patient benefit.
25. It is expected that the awards will help establish new and consolidate existing collaborations between clinical and academic experts from a wide range of fields, including AI and data science, social science, and health and care services, public health and epidemiology. Funded projects should be delivered by cross-disciplinary teams capable of linking up and working with relevant groups and initiatives at a national and international level. The type and number of disciplines represented within funded Research Collaborations will depend on the research questions being answered. We encourage cross-institution working but it is not mandated in this call.
26. It is expected that all data generated or curated within this funded programme are made accessible to the broad scientific community. Successful Research Collaborations will be expected to support the creation of a nation-wide integrated health data resource. Existing data used in the proposed research, as well as any new data generated using these funds, should be made available through the currently developed Health Data Research Innovation Gateway, where possible. Plans for making data widely available for future research should be outlined.
27. We expect all development award holders and all Research Collaborations to subscribe to the Health Data Research UK Alliance’s Terms & Conditions on information governance, ethics, intellectual property rights and commercial models. Subscription to the Alliance Principles of Participation and membership of the Alliance is strongly encouraged. Applicants who don’t wish to subscribe should provide clear justification of the alternative mechanism by which they intend to make their data discoverable and accessible for all. Information on how applicants can become a member of the Alliance is available on the Health Data Research UK website.
28. All research funded by the NIHR should contribute to reducing health inequalities, defined as the systematic differences in health which exist between different population groups, including but not limited to: social class, ethnicity, sex and other protected groups. Health inequalities can manifest at multiple levels and the choice of data sources need to be carefully considered for any potential bias that might exacerbate health inequalities. Research funded under this call should contribute towards equality in health outcomes.
29. Applicants should consider the full range of potential audiences and describe how the research findings could be disseminated most effectively to ensure that the lessons from this research are fed back into the research pipeline to consider underpinning mechanisms and to impact on policy and practice in the health and care system.
30. As part of their proposal, applicants should explain what they believe will be the key risks to delivering their research, and what contingencies they will put in place to deal with them.
31. Applicants are required to have clearly articulated Patient and Public Involvement (PPI) plans for continuous interactions with patient groups throughout the project (please see section below for more details).
32. Alongside the funding for this call we will establish a centralised expert Research Support Facility for award holders. The aims of the facility are anticipated to include:
- support for Research Collaborations with technical AI and data science expertise;
- support for data access and linkage where feasible and to represent a united voice for this programme in wider discussions with stakeholders on barriers to data access and data quality;
- building capability across multi-disciplinary teams including working with existing NIHR facilities on professional development opportunities for early and mid-career researchers and developing capacity in the MLTC-M field; and
- developing a research community and fostering shared learning and synergies within the AIM call and across wider programmes of work on MLTC-M.
- The specification for this facility is being drafted and we aim to launch an expression of interest for the call in July.
33. The specification for this facility is being drafted and we aim to launch an expression of interest for the call in July.
34. Research Collaborations will be expected to work together with the Research Support Facility on these aims. Applicants should demonstrate a strong intention to work with other successful groups funded by this call to create synergies between research projects; and share learning and expertise across consortia through the Research Support Function. Applicants should outline how their skills, resources or expertise might be used to support the wider network of Research Collaborations. Applicants short-listed at Stage 1 of the commissioning process will have the opportunity to re-calibrate their proposals at Stage 2 to take into account the RSF offering.
35. We expect the Research Collaborations to work together to build capacity and capability among early and mid-career researchers and seek to bring in researchers who do not yet identify as MLTC-M researchers. Applicants are required to describe their approach to achieving these objectives and how they would aim to work with a Research Support Function to deliver this.
Proposals
36. The core funding for this call will be allocated between two aligned streams:
Research Collaborations
£2.5-5m is available for Research Collaborations delivered over a period of up to 36 months. Collaborations are expected to:
- comprise a number of high-quality interrelated projects that form a coherent theme, where added value is gained from the combination of the various strands of research;
- create a portfolio of research which includes innovation but balances possible risk allowing for learning through failure;
- use a range of multidisciplinary and methodological approaches, providing a critical mass of multi-disciplinary experts with the capacity to provide a long-term research resource and develop expertise and research capacity within and relevant to the health and social care systems;
- demonstrate clear trajectory towards patient or health system benefits;
- demonstrate how it considers and responds to burden of disease by population and geography and addresses issues relating to equality, inclusion and diversity; and
- include clear plans for implementation, knowledge mobilisation and dissemination, contributing towards a step change to further research, practice and/or outcomes. Collaborations should demonstrate the ability to operate across a wide range of stakeholders to influence agendas and system changes, working with the Research Support Facility.
Development Awards
Up to £120k for up to 8 months is available to undertake preparatory work to develop a future programme of research (e.g. develop collaborations, data access and linking, proof of concept/feasibility work) but broader ranging development work is permitted. Applicants should be able to demonstrate the ability to start by January 2021. Proposals should clearly describe how the preparatory work will inform the development of a future Research Collaboration. Development Award holders will apply directly for stage 2 in the next phase of the Research Collaborations competition (wave 2).
Eligibility
37. The lead organisation must be either: (a) an NHS organisation (including NHS Trusts and NHS Foundation Trusts) or equivalent UK authorities, or (b) a university, research institutes or not-for-profit organisation. In addition to these lead organisations SMEs (including start-up or ‘spin-out’ companies) are also eligible to receive funding. If an appropriate case is made, then overseas university partners are permissible and may receive funding. We would expect the application to make a strong case that the chosen overseas academic partner was the organisation best placed to provide input to the planned research.
38. Specialist services or expertise may be brought into the team through consultancy or sub-contract arrangements; however, appropriate justification must be provided. Sub-contractors may be based outside of England. The day-to-day running of the project should be handled through a project manager. While it is acceptable for the lead applicant to act as the project manager, for large Research Collaborations in particular, we would expect the lead organisation to provide dedicated project management support. The NIHR will verify on a regular basis that successful applicants have access to adequate, dedicated management support.
39. Large companies may be involved but are ineligible for funding. For all collaborations where a partner is providing in-kind contributions, the exact nature of the commitment of each partner must be clearly detailed.
40. If the application is successful, a contract will be placed with the lead organisation for delivery of the research.
Patient and Public Involvement
41. The NIHR expects the active involvement of patients and the public (e.g. service users and carers) in the research that it supports, where appropriate. However, the nature and extent of patient and public involvement (PPI) is likely to vary depending on the context of the study. Applicants should describe how the issue of PPI will be addressed throughout the research process. For example, this could include patient and public involvement in refining research questions, designing research instruments, advising on approaches to recruitment, assisting in the collection and analysis of data, participation or chairing advisory and steering groups, and in the dissemination of research findings.
42. Applicants are required to detail what active involvement is planned, how it will benefit the research and the rationale for their approach. PPI needs to be undertaken in a manner that acknowledges that some people may need additional support, or to acquire new knowledge or skills to enable them to become involved effectively (see INVOLVE publications for guides for researchers). Applicants should therefore provide information on arrangements for training and support. Where no PPI is proposed, a rationale for this decision must be given.
43. For further information and guidance about PPI, please visit the PPI advice in the researchers section on the NIHR website.
Assessment criteria
44. Applicants are expected to include in their application relevant information in line with the assessment criteria outlined below.
Relevance of the proposed research to the research specification
- How relevant is the proposal in relation to the research brief? Does it address the call’s strategic objectives (e.g. capacity and capability development development; consideration of health inequalities and PPI; methodological development etc.)?
- Does the application demonstrate an awareness and understanding of previous relevant research or developments in this area?
- To what extent does the proposed research add distinct value or advance existing knowledge?
Quality of the research design
- How appropriate is the research design in relation to the stated objectives?
- To what extent is the proposed design and methodology for all elements of the research well defined, appropriate, valid and feasible within the timeframe and resources requested?
- To what extent does the research show originality and innovation?
- To what extent does the proposed work add to or complement initiatives at a national/international level?
Quality of the work plan and proposed management arrangements
- Are work packages coherent, fully justified, and aligned with the overall vision of the proposal?
- How appropriate are the work plan and management arrangements? Have clear milestones been proposed? How likely is it that these will be met within the specified timeframe?
- Have the applicants identified key risks to delivery (e.g. ethical, technical, and organisational)? Have these been adequately addressed?
- Have the applicants already secured access to relevant sources of evidence and data sets required to perform the research? Are governance and data management arrangements robust?
Strength of the collaboration leadership and research team
- Does the Principal Investigator appear suitably qualified and experienced to lead the proposed work? Are the leadership and management arrangements convincing and coherent?
- Are the roles of the team members clearly described?
- Does the research team provide the necessary breadth and depth of expertise to deliver the proposed work?
- Have the applicants proposed what they can offer to support the wider network of Research Collaborations and how they will collaborate with the Research Support Facility? To what extent are these likely to add value to the AIM investment?
Impact of the proposed work
- Does the proposal offer a clear vision for benefits to patients and the health system in the context of MLTC-M?
- Are the necessary clinical, academic, organisational links needed to support the research in place?
- Are dissemination and stakeholder engagement plans clearly described and credible? Are the identified audiences appropriate and their needs considered? Are there specific resources and competencies dedicated to these activities?
- Does the proposal outline credible plans to make data available and share learning with the wider health research community?
- Are there credible plans for the implementation of patient and public involvement? Are these resourced?
Value for money
- Does the proposal sufficiently justify the resources required to deliver the proposed work?
- Do the proposed costs demonstrate value for money?
- Is the time committed by the applicants realistic to ensure delivery?
Patient and public involvement
- Have the applicants carefully considered ways to embed input from patients and the public in the definition of research priorities and the delivery of the research?
- Are adequate, well justified training and support measures for PPI representatives described in the proposal?
- Does the budget reflect the proposed research ambitions for PPI?
Timeline
45. The full timeline for AIM Research Collaborations (2-stage process) wave one is as follows:
| Step | Date |
|---|---|
| Stage 1 Launch | June 2020 |
| Engagement events for applicants | July 2020 |
| Stage 1 close | September 2020 |
| Stage 1 Committee Meeting | November 2020 |
| Stage 2 Launch | November 2020 |
| Stage 2 Close | February 2021 |
| Stage 2 Committee Meeting | April 2021 |
| Outcomes | April 2021 |
| Expected projects start | June 2021 |
46. The full timeline for AIM Development Awards (single stage) is as follows:
| Step | Date |
|---|---|
| Stage 1 Launch | June 2020 |
| Engagement events for applicants | July 2020 |
| Stage 1 close | September 2020 |
| Committee Meeting | November 2020 |
| Outcomes | November 2020 |
| Expected projects start | January 2021 |
Budget and duration
47. The NIHR is expecting to fund between 4-6 Research Collaborations. The range for this award is £2.5-5m for up to 36 months for wave one (£2.5-4m at 30 months at wave two). We encourage applications of varying scale, duration and objectives as suits the research aims of the specific alliance and their research programme. We are looking to fund a balanced portfolio of Research Collaborations. The funding requested needs to be proportionate to the research aims and questions of the work programme.
48. Costing can include up to 80% full economic costing (FEC) but should exclude VAT. Applicants are advised that value for money is one of the key criteria used by peer reviewers and funding committee members to assess applications.
49. Capability to start promptly will be an advantage and for this commissioning round, applicants should be able demonstrate that Research Collaborations can start between June and July 2021. Wave one Development Awards are expected to start by January 2021.
Management arrangements
50. A research advisory group including representatives of a range of stakeholder groups, including the NIHR, 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
Standard information for applicants
1. The sections below provide standard information on different aspects of NIHR funding and will contain details relevant to your application.
General comments about applications
2. Applications will be considered from other UK countries (Scotland, Wales and Northern Ireland) provided they address the priority areas in a way that is relevant to the needs of the Department of Health and Social Care (England) and meet all other selection criteria.
3. Applicants are encouraged to submit multidisciplinary applications.
4. Applicants should consider the full range of potential audiences and describe how the research findings could be disseminated most effectively to ensure that the lessons from this research impact on policy and practice.
Research governance
5. Day-to-day management of this research will be provided by the principal investigator. They and their employers should ensure that they identify, and are able to discharge effectively, their respective responsibilities under the Health Research Authority (HRA) UK Policy Framework for Health and Social Care Research, which sets out the broad principles of good research governance.
6. All successful research involving National Health Service (NHS) and social care users, carers, staff, data and/or premises must be approved by the appropriate research ethics committee (REC) or social care research ethics committee (SCREC). For further information on RECs, please visit the HRA website.
7. The successful research team must adhere to the General Data Protection Regulation and the new Data Protection Act (2018) and the Freedom of Information Act (2000). Effective security management, and ensuring personal information and assessment data are kept secure, will be essential. In particular:
- The research team shall, at all times, be responsible for ensuring that data (including data in any electronic format) are stored securely. The research team shall take appropriate measures to ensure the security of such data, and guard against unauthorised access thereto, disclosure thereof, or loss or destruction while in its custody.
- Personal data shall not be made available to anyone other than those employed directly on the project by the research team, to the extent that they need access to such information for the performance of their duties.
8. For any research involving clinical trials, the successful team will be expected to be familiar with the Medical Research Council (MRC) Framework for Evaluating Complex Interventions, and to follow the principles of the MRC Guidelines for Good Clinical Practice in Clinical Trials in proposing structures for oversight of such trials and comply with the Medicines for Human Use (Clinical Trials) Regulations 2004.
9. The Institution leading the proposal should confirm that it has the capacity and is prepared to take on sponsorship responsibilities for clinical trials undertaken as part of the programme. Where the proposal includes a proposal for multi-site clinical trial activities the research unit should demonstrate that they have the experience of governance and management of clinical trials across multiple clinical trial sites.
Risk management
10. Applicants should submit, as part of their proposal, a summary explaining what they believe will be the key risks to delivering their research, and what contingencies they will put in place to deal with them.
11. A risk is defined as any factor which may delay, disrupt or prevent the full achievement of a project objective. All risks should be identified. The summary should include an assessment of each risk, together with a rating of the risks likelihood and its impact on a project objective (using a high, medium or low classification for both). The risk assessment should also identify appropriate actions that would reduce or eliminate each risk, or its impact.
12. Typical areas of risk for an evaluation study might include ethical approval, site variation in data gathering, staffing, resource constraints, technical constraints, data access and quality, timing, management and operational issues; however, please note this is not an exhaustive list.
Outputs and reporting arrangements
13. The research team will be expected to provide regular progress reports over the lifetime of the research and will be provided with a progress report template to complete at regular intervals. In addition to describing progress, these reports will allow researchers to indicate any significant changes to the agreed protocol, as well as setting down milestones for the next reporting period, giving an update on PPI and any publications or other outputs. Information on emergent findings that can feed more immediately into policy development will be encouraged and should be made available as appropriate.
14. Where applicable, a final report on the research, with an accessible executive summary, will be required within one month following completion of the research. The report may be peer reviewed and may be circulated among relevant stakeholders within the Department of Health and Social Care and its partners. A summary of the final report will be placed in the public domain. Outputs resulting from expenditure of public funds are made available for public scrutiny so it is important that the summary of your final report is easily accessible to the lay reader.
Dissemination
15. Applicants should describe how the research findings could be disseminated most effectively, ensuring that results of this research impact on policy and practice in the NHS, DHSC, social care and wider sectors.
16. Publication of scientifically robust research results is encouraged. This could include plans to submit papers to peer reviewed journals, national and regional conferences aimed at service providers, professional bodies and professional leaders. It might also include distribution of executive summaries and newsletters. Less traditional dissemination routes are also welcomed for consideration.
Transparency
17. In line with the government’s transparency agenda, any contract resulting from this tender may be published in its entirety to the general public. Further information on the transparency agenda is available in the government's procurement and contracting transparency requirements guidance.
18. Details of the standard terms and conditions of the NIHR contract are available on the contracts and intellectual property page on NIHR website.
Application process
19. The NIHR runs an online application process and all applications must be submitted electronically. No applications will be accepted that are submitted by any means other than the online process. Deadlines for the submission of outline and full research applications occur at 1.00 pm on the day indicated and no applications can be accepted after this deadline.
20. We strongly recommend that you submit your application on the day before. Once the 1.00 pm deadline passes, the system shuts down automatically and NIHR Programme Managers are unable to re-open it. If you are experiencing any technical difficulties submitting your application, please contact the AIM Team via the online enquiry form (please ensure that you leave a contactable phone number and a member of the team will get back to you in good time) before 1.00 pm on a closing date.
21. Applicants are expected, before submitting applications, to have discussed their applications with their own and any other body whose cooperation will be required in conducting the research.
22. In order for your full application to be validated and submitted you are required to gain electronic approval from the relevant authorities before the application deadline. The Declarations page must be approved:
- by the Lead Applicant to confirm that the content of the application is complete and correct.
- by an administrative or finance officer for the contracting (host) institution to confirm that the financial details of the application are correct and that the host institution .agrees to administer the award if made.
- by a Head of Department or Senior Manager to confirm that they have read the application and that, if funded, the work will be accommodated and administered in the named institution and that the applicants may undertake the work.
23. Until this is completed the lead applicant is unable to validate and submit the application.
Commissioning process
24. In standard 2 stage commissioning, outline applications will be shortlisted by a Funding Committee. The Committee will make recommendations that will be ratified by the Department of Health and Social Care (DHSC). Incomplete applications, applications too remote from the issues set out in the research specification, or applications that have clearly inadequate presentation or methods may be rejected at this stage.
25. Applications that are successfully shortlisted by the Funding Committee will proceed to Stage 2 of the application process and will be invited to submit a Stage 2 full application for consideration.
26. All AIM Research Collaboration submissions will be peer-reviewed by both stakeholder and independent academic referees. Wherever time permits, applicants will be given one week to respond to the peer reviewers’ comments.
27. Full applications, peer reviewers’ comments and any responses to those comments will then be considered by the Funding Committee, which is composed of independent experts (possibly with observers from government departments and executive agencies), who will advise the NIHR on which applications are most suited to receive funding. The Committee will be informed by the reviewers’ comments and any responses made to these comments by the researchers. However, it is ultimately the responsibility of the Committee to make any funding recommendations to the NIHR and the DHSC.
Contacts
28. General enquiries regarding the application and commissioning process can be directed to the AIM Team via the online enquiry form. Please ensure that you leave a contactable phone number and a member of the team will get back to you.
References
- Government Digital Service and Office for Artificial Intelligence. A guide to using artificial intelligence in the public sector. June 2019.
- Barnett et al. (2012) Epidemiology of multimorbidity and implications for health care, and medical education: a cross-sectional study. The Lancet, 380(9836), 37-43.
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