Multidisciplinary ecosystem to study lifecourse determinants and prevention of early-onset burdensome multimorbidity (MELD-B) – protocol for a research collaboration
Background Most people living with multiple long-term condition multimorbidity (MLTC-M) are under 65 (defined as ‘early onset’). Earlier and greater accrual of long-term conditions (LTCs) may be influenced by the timing and nature of exposure to key risk factors, wider determinants or other LTCs at...
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2023-09-01
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| Series: | Journal of Multimorbidity and Comorbidity |
| Online Access: | https://doi.org/10.1177/26335565231204544 |
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| _version_ | 1846157906537349120 |
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| author | Simon DS Fraser Sebastian Stannard Emilia Holland Michael Boniface Rebecca B Hoyle Rebecca Wilkinson Ashley Akbari Mark Ashworth Ann Berrington Roberta Chiovoloni Jessica Enright Nick A Francis Gareth Giles Martin Gulliford Sara Macdonald Frances S Mair Rhiannon K Owen Shantini Paranjothy Heather Parsons Ruben J Sanchez-Garcia Mozhdeh Shiranirad Zlatko Zlatev Nisreen Alwan |
| author_facet | Simon DS Fraser Sebastian Stannard Emilia Holland Michael Boniface Rebecca B Hoyle Rebecca Wilkinson Ashley Akbari Mark Ashworth Ann Berrington Roberta Chiovoloni Jessica Enright Nick A Francis Gareth Giles Martin Gulliford Sara Macdonald Frances S Mair Rhiannon K Owen Shantini Paranjothy Heather Parsons Ruben J Sanchez-Garcia Mozhdeh Shiranirad Zlatko Zlatev Nisreen Alwan |
| author_sort | Simon DS Fraser |
| collection | DOAJ |
| description | Background Most people living with multiple long-term condition multimorbidity (MLTC-M) are under 65 (defined as ‘early onset’). Earlier and greater accrual of long-term conditions (LTCs) may be influenced by the timing and nature of exposure to key risk factors, wider determinants or other LTCs at different life stages. We have established a research collaboration titled ‘MELD-B’ to understand how wider determinants, sentinel conditions (the first LTC in the lifecourse) and LTC accrual sequence affect risk of early-onset, burdensome MLTC-M, and to inform prevention interventions. Aim Our aim is to identify critical periods in the lifecourse for prevention of early-onset, burdensome MLTC-M, identified through the analysis of birth cohorts and electronic health records, including artificial intelligence (AI)-enhanced analyses. Design We will develop deeper understanding of ‘burdensomeness’ and ‘complexity’ through a qualitative evidence synthesis and a consensus study. Using safe data environments for analyses across large, representative routine healthcare datasets and birth cohorts, we will apply AI methods to identify early-onset, burdensome MLTC-M clusters and sentinel conditions, develop semi-supervised learning to match individuals across datasets, identify determinants of burdensome clusters, and model trajectories of LTC and burden accrual. We will characterise early-life (under 18 years) risk factors for early-onset, burdensome MLTC-M and sentinel conditions. Finally, using AI and causal inference modelling, we will model potential ‘preventable moments’, defined as time periods in the life course where there is an opportunity for intervention on risk factors and early determinants to prevent the development of MLTC-M. Patient and public involvement is integrated throughout. |
| format | Article |
| id | doaj-art-bcab6518375d40b2be0adf70b50e44bf |
| institution | Kabale University |
| issn | 2633-5565 |
| language | English |
| publishDate | 2023-09-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Journal of Multimorbidity and Comorbidity |
| spelling | doaj-art-bcab6518375d40b2be0adf70b50e44bf2024-11-25T00:03:45ZengSAGE PublishingJournal of Multimorbidity and Comorbidity2633-55652023-09-011310.1177/26335565231204544Multidisciplinary ecosystem to study lifecourse determinants and prevention of early-onset burdensome multimorbidity (MELD-B) – protocol for a research collaborationSimon DS FraserSebastian StannardEmilia HollandMichael BonifaceRebecca B HoyleRebecca WilkinsonAshley AkbariMark AshworthAnn BerringtonRoberta ChiovoloniJessica EnrightNick A FrancisGareth GilesMartin GullifordSara MacdonaldFrances S MairRhiannon K OwenShantini ParanjothyHeather ParsonsRuben J Sanchez-GarciaMozhdeh ShiraniradZlatko ZlatevNisreen AlwanBackground Most people living with multiple long-term condition multimorbidity (MLTC-M) are under 65 (defined as ‘early onset’). Earlier and greater accrual of long-term conditions (LTCs) may be influenced by the timing and nature of exposure to key risk factors, wider determinants or other LTCs at different life stages. We have established a research collaboration titled ‘MELD-B’ to understand how wider determinants, sentinel conditions (the first LTC in the lifecourse) and LTC accrual sequence affect risk of early-onset, burdensome MLTC-M, and to inform prevention interventions. Aim Our aim is to identify critical periods in the lifecourse for prevention of early-onset, burdensome MLTC-M, identified through the analysis of birth cohorts and electronic health records, including artificial intelligence (AI)-enhanced analyses. Design We will develop deeper understanding of ‘burdensomeness’ and ‘complexity’ through a qualitative evidence synthesis and a consensus study. Using safe data environments for analyses across large, representative routine healthcare datasets and birth cohorts, we will apply AI methods to identify early-onset, burdensome MLTC-M clusters and sentinel conditions, develop semi-supervised learning to match individuals across datasets, identify determinants of burdensome clusters, and model trajectories of LTC and burden accrual. We will characterise early-life (under 18 years) risk factors for early-onset, burdensome MLTC-M and sentinel conditions. Finally, using AI and causal inference modelling, we will model potential ‘preventable moments’, defined as time periods in the life course where there is an opportunity for intervention on risk factors and early determinants to prevent the development of MLTC-M. Patient and public involvement is integrated throughout.https://doi.org/10.1177/26335565231204544 |
| spellingShingle | Simon DS Fraser Sebastian Stannard Emilia Holland Michael Boniface Rebecca B Hoyle Rebecca Wilkinson Ashley Akbari Mark Ashworth Ann Berrington Roberta Chiovoloni Jessica Enright Nick A Francis Gareth Giles Martin Gulliford Sara Macdonald Frances S Mair Rhiannon K Owen Shantini Paranjothy Heather Parsons Ruben J Sanchez-Garcia Mozhdeh Shiranirad Zlatko Zlatev Nisreen Alwan Multidisciplinary ecosystem to study lifecourse determinants and prevention of early-onset burdensome multimorbidity (MELD-B) – protocol for a research collaboration Journal of Multimorbidity and Comorbidity |
| title | Multidisciplinary ecosystem to study lifecourse determinants and prevention of early-onset burdensome multimorbidity (MELD-B) – protocol for a research collaboration |
| title_full | Multidisciplinary ecosystem to study lifecourse determinants and prevention of early-onset burdensome multimorbidity (MELD-B) – protocol for a research collaboration |
| title_fullStr | Multidisciplinary ecosystem to study lifecourse determinants and prevention of early-onset burdensome multimorbidity (MELD-B) – protocol for a research collaboration |
| title_full_unstemmed | Multidisciplinary ecosystem to study lifecourse determinants and prevention of early-onset burdensome multimorbidity (MELD-B) – protocol for a research collaboration |
| title_short | Multidisciplinary ecosystem to study lifecourse determinants and prevention of early-onset burdensome multimorbidity (MELD-B) – protocol for a research collaboration |
| title_sort | multidisciplinary ecosystem to study lifecourse determinants and prevention of early onset burdensome multimorbidity meld b protocol for a research collaboration |
| url | https://doi.org/10.1177/26335565231204544 |
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