From 5a531bd3ae46f334329f9b22116e1b3c71b6761b Mon Sep 17 00:00:00 2001 From: Batool Almarzouq <53487593+BatoolMM@users.noreply.github.com> Date: Mon, 4 Mar 2024 10:15:44 +0000 Subject: [PATCH 1/6] Add COMPUTE --- docs/pages/aim-projects.md | 28 ++++++++++++++++++++++++++++ 1 file changed, 28 insertions(+) diff --git a/docs/pages/aim-projects.md b/docs/pages/aim-projects.md index 9114ba5..04969d0 100644 --- a/docs/pages/aim-projects.md +++ b/docs/pages/aim-projects.md @@ -184,6 +184,34 @@ Our ‘People, Policy and Impact’ group will share our learning and influence * You can read more about the MELD-B project on their page at [University of Southampton - MELD-B](https://www.southampton.ac.uk/publicpolicy/support-for-policymakers/policy-projects/Current%20projects/meld-b.page) or in their first blog post which you can find here: [University of Southampton - MELD-B Introductory Blog](https://www.southampton.ac.uk/publicpolicy/support-for-policymakers/blogs/evidence-to-policy-blog/meld-b-blog.page) +## CoMPuTE + +> The Complex Multiple long-term conditions Phenotypes, Trends, and Endpoints (CoMPuTE) project is funded by the National Institute for Health and Care Research (NIHR) under its Programme Grants for Applied Research Programme (NIHR204406). It is based on the University of Oxford, University of Leeds and University College London. + +### Background to the CoMPuTE project + +More than a quarter of adults in England have more than one health condition. By 2035 this is expected to increase by 10-17%. Having more than one condition is called ‘multiple long-term conditions’ (MLTC). The more conditions someone has, the more disabling the effects. + +MLTC is difficult for both patients and carers: taking more medicines (with possible problems caused by conflicting or simply too many medications); the cost and wasted time of attending too many healthcare appointments; and the day-to-day challenges of living with multiple conditions. + +This study hopes to predict who will suffer from MLTC and how MLTC will progress over a person’s lifetime. Previous research has focused on looking at causes of MLTC, however much is still unknown about why certain conditions appear together, how they relate to normal ageing, prevention, and appropriate care. Also, although the NHS currently invests significant amounts of money in trying to prevent specific health conditions (e.g. heart disease, cancer), many people do not engage. This is a missed opportunity to prevent future ill health. + +### The CoMPuTE Research Aims + +This project looks at whether using artificial intelligence (AI) can help us predict those more likely to develop MLTC – to get help sooner to those who need it and prevent people developing MLTC in the first place. + +Regular computer models are already used for research on electronic health records. We want to use AI techniques to process this information faster and more accurately. The data will be ‘anonymised’ so it cannot be traced to individuals. Because many people have concerns about how their data are used, members of the public have been involved in this work from the beginning and will be involved throughout. A public member leads one section of work. Other public members work on an equal level with the academic researchers. + +- This study hopes to see whether it is possible to predict who will suffer from MLTC and how MLTC will progress over a person’s lifetime. +- It will investigate inequalities and the health and financial burden of MLTC. +- It brings in the public perspective on ethical and social questions about the use of AI in healthcare. Members of often-excluded communities will be actively involved in discussion groups, the development of study materials and the writing of papers. This is important to ensure that plans to help people with MLTC address everyone’s health and care needs. + +### How CoMPuTE will involve patients and members of the public + +The amount of public participation and leadership in this project makes it unique. One-third of the project is entirely public-led. + +We believe that this project will become an example of best practice in knitting together cutting-edge technology with ethical reflection and public involvement, and help to develop new approaches to care which reduce the number of people developing MLTC. + ## AI-MIXED Cluster > Information coming soon. From 5953664bfb476db0ee5614e268b50111dfaca4c8 Mon Sep 17 00:00:00 2001 From: Batool Almarzouq <53487593+BatoolMM@users.noreply.github.com> Date: Mon, 4 Mar 2024 10:40:32 +0000 Subject: [PATCH 2/6] Update docs/pages/aim-projects.md Co-authored-by: Bastian Greshake Tzovaras --- docs/pages/aim-projects.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/pages/aim-projects.md b/docs/pages/aim-projects.md index 04969d0..eb36b48 100644 --- a/docs/pages/aim-projects.md +++ b/docs/pages/aim-projects.md @@ -186,7 +186,7 @@ Our ‘People, Policy and Impact’ group will share our learning and influence ## CoMPuTE -> The Complex Multiple long-term conditions Phenotypes, Trends, and Endpoints (CoMPuTE) project is funded by the National Institute for Health and Care Research (NIHR) under its Programme Grants for Applied Research Programme (NIHR204406). It is based on the University of Oxford, University of Leeds and University College London. +> The CoMPuTE project uses Artificial Intelligence to help predict who is more likely to develop multiple long-term conditions. The project is funded by the National Institute for Health and Care Research (NIHR) under its Programme Grants for Applied Research Programme (NIHR204406). It is based on the University of Oxford, University of Leeds and University College London. ### Background to the CoMPuTE project From cc25a02e8ac01a95cf6191f32c0c78092fc1d8ca Mon Sep 17 00:00:00 2001 From: Batool Almarzouq <53487593+BatoolMM@users.noreply.github.com> Date: Mon, 4 Mar 2024 10:40:40 +0000 Subject: [PATCH 3/6] Update docs/pages/aim-projects.md Co-authored-by: Bastian Greshake Tzovaras --- docs/pages/aim-projects.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/pages/aim-projects.md b/docs/pages/aim-projects.md index eb36b48..032061a 100644 --- a/docs/pages/aim-projects.md +++ b/docs/pages/aim-projects.md @@ -192,7 +192,7 @@ Our ‘People, Policy and Impact’ group will share our learning and influence More than a quarter of adults in England have more than one health condition. By 2035 this is expected to increase by 10-17%. Having more than one condition is called ‘multiple long-term conditions’ (MLTC). The more conditions someone has, the more disabling the effects. -MLTC is difficult for both patients and carers: taking more medicines (with possible problems caused by conflicting or simply too many medications); the cost and wasted time of attending too many healthcare appointments; and the day-to-day challenges of living with multiple conditions. +MLTC are difficult for both patients and carers: taking more medicines (with possible problems caused by conflicting or simply too many medications); the cost and wasted time of attending too many healthcare appointments; and the day-to-day challenges of living with multiple conditions. This study hopes to predict who will suffer from MLTC and how MLTC will progress over a person’s lifetime. Previous research has focused on looking at causes of MLTC, however much is still unknown about why certain conditions appear together, how they relate to normal ageing, prevention, and appropriate care. Also, although the NHS currently invests significant amounts of money in trying to prevent specific health conditions (e.g. heart disease, cancer), many people do not engage. This is a missed opportunity to prevent future ill health. From 5928a0c518737fa393faa4d5c00d685e03a48278 Mon Sep 17 00:00:00 2001 From: Batool Almarzouq <53487593+BatoolMM@users.noreply.github.com> Date: Mon, 4 Mar 2024 12:08:30 +0000 Subject: [PATCH 4/6] Update aim-projects.md --- docs/pages/aim-projects.md | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/docs/pages/aim-projects.md b/docs/pages/aim-projects.md index 032061a..a057a40 100644 --- a/docs/pages/aim-projects.md +++ b/docs/pages/aim-projects.md @@ -186,7 +186,7 @@ Our ‘People, Policy and Impact’ group will share our learning and influence ## CoMPuTE -> The CoMPuTE project uses Artificial Intelligence to help predict who is more likely to develop multiple long-term conditions. The project is funded by the National Institute for Health and Care Research (NIHR) under its Programme Grants for Applied Research Programme (NIHR204406). It is based on the University of Oxford, University of Leeds and University College London. +> The The Complex Multiple long-term conditions Phenotypes, Trends, and Endpoints (CoMPuTE) project uses Artificial Intelligence to help predict who is more likely to develop multiple long-term conditions. The project is funded by the National Institute for Health and Care Research (NIHR) under its Programme Grants for Applied Research Programme (NIHR204406). It is based on the University of Oxford, University of Leeds and University College London. ### Background to the CoMPuTE project @@ -208,9 +208,7 @@ Regular computer models are already used for research on electronic health recor ### How CoMPuTE will involve patients and members of the public -The amount of public participation and leadership in this project makes it unique. One-third of the project is entirely public-led. - -We believe that this project will become an example of best practice in knitting together cutting-edge technology with ethical reflection and public involvement, and help to develop new approaches to care which reduce the number of people developing MLTC. +One-third of the project is entirely public-led. We believe that this project will become an example of best practice in knitting together cutting-edge technology with ethical reflection and public involvement, and help to develop new approaches to care which reduce the number of people developing MLTC. ## AI-MIXED Cluster From 1bf9c6d938e38d0018c0d260b41f158fc5ae6cd2 Mon Sep 17 00:00:00 2001 From: Batool Almarzouq <53487593+BatoolMM@users.noreply.github.com> Date: Mon, 4 Mar 2024 12:17:34 +0000 Subject: [PATCH 5/6] Update aim-projects.md --- docs/pages/aim-projects.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/pages/aim-projects.md b/docs/pages/aim-projects.md index a057a40..bca7c56 100644 --- a/docs/pages/aim-projects.md +++ b/docs/pages/aim-projects.md @@ -186,7 +186,7 @@ Our ‘People, Policy and Impact’ group will share our learning and influence ## CoMPuTE -> The The Complex Multiple long-term conditions Phenotypes, Trends, and Endpoints (CoMPuTE) project uses Artificial Intelligence to help predict who is more likely to develop multiple long-term conditions. The project is funded by the National Institute for Health and Care Research (NIHR) under its Programme Grants for Applied Research Programme (NIHR204406). It is based on the University of Oxford, University of Leeds and University College London. +> The Complex Multiple long-term conditions Phenotypes, Trends, and Endpoints (CoMPuTE) project uses Artificial Intelligence to help predict who is more likely to develop multiple long-term conditions. The project is funded by the National Institute for Health and Care Research (NIHR) under its Programme Grants for Applied Research Programme (NIHR204406). It is based on the University of Oxford, University of Leeds and University College London. ### Background to the CoMPuTE project @@ -198,7 +198,7 @@ This study hopes to predict who will suffer from MLTC and how MLTC will progress ### The CoMPuTE Research Aims -This project looks at whether using artificial intelligence (AI) can help us predict those more likely to develop MLTC – to get help sooner to those who need it and prevent people developing MLTC in the first place. +This project looks at whether using artificial intelligence (AI) can help us predict those more likely to develop MLTC – to get help sooner to those who need it and prevent people from developing MLTC in the first place. Regular computer models are already used for research on electronic health records. We want to use AI techniques to process this information faster and more accurately. The data will be ‘anonymised’ so it cannot be traced to individuals. Because many people have concerns about how their data are used, members of the public have been involved in this work from the beginning and will be involved throughout. A public member leads one section of work. Other public members work on an equal level with the academic researchers. From 6f5d625b37accc785e00df3901102e44d5be2c10 Mon Sep 17 00:00:00 2001 From: Batool Almarzouq <53487593+BatoolMM@users.noreply.github.com> Date: Thu, 7 Mar 2024 07:05:48 +0000 Subject: [PATCH 6/6] Update aim-projects.md --- docs/pages/aim-projects.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/docs/pages/aim-projects.md b/docs/pages/aim-projects.md index bca7c56..db00fb5 100644 --- a/docs/pages/aim-projects.md +++ b/docs/pages/aim-projects.md @@ -208,7 +208,9 @@ Regular computer models are already used for research on electronic health recor ### How CoMPuTE will involve patients and members of the public -One-third of the project is entirely public-led. We believe that this project will become an example of best practice in knitting together cutting-edge technology with ethical reflection and public involvement, and help to develop new approaches to care which reduce the number of people developing MLTC. +One of the three CoMPuTE Themes (Ethics, Patients and the Public’) is entirely public-led and aims to adopt best practices and break new ground in public and patient involvement in directing the research. Our public stakeholder group brings a wide range of competencies and experience, including personal, geographical, ethnic, socio-economic and age diversity and lived experience of the immigrant experience and living with MLTC, and professional competencies in engineering, randomised control trials, medical communication, project management and health care delivery, to name a few. + +Public members are linked with the data and epidemiology Themes (Themes 1 and 2) and are increasingly embedded in that work. Public members have already helped shift the direction of research. Public members already work with and will be presenting to researchers within and beyond the programme; we are planning a series of public-led mini-webinar; our public members will be co-authoring papers, and they will be forging the broader dissemination strategy. ## AI-MIXED Cluster