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28/07/2017 01:53

Publication Details

This article is open access.

MODEM: A comprehensive approach to modelling outcome and costs impacts of interventions for dementia. Protocol paper
Comas-Herrera A, Knapp M, Wittenberg R, Banerjee S, Bowling A, Grundy E, Jagger C, Farina N, Lombard D, Lorenz K, McDaid D (2017)
BMC Health Services Research 17 17:25
DOI: http://dx.doi.org/10.1186/s12913-016-1945-x (available online 11 January 2017)
Abstract:

Background. The MODEM project (A comprehensive approach to MODelling outcome and costs impacts of interventions for DEMentia) explores how changes in arrangements for the future treatment and care of people living with dementia, and support for family and other unpaid carers, could result in better outcomes and more efficient use of resources.

Methods. MODEM starts with a systematic mapping of the literature on effective and (potentially) cost-effective interventions in dementia care. Those findings, as well as data from a cohort, will then be used to model the quality of life and cost impacts of making these evidence-based interventions more widely available in England over the period from now to 2040. Modelling will use a suite of models, combining microsimulation and macrosimulation methods, modelling the costs and outcomes of care, both for an individual over the life-course from the point of dementia diagnosis, and for individuals and England as a whole in a particular year.

Project outputs will include an online Dementia Evidence Toolkit, making evidence summaries and a literature database available free to anyone, papers in academic journals and other written outputs, and a MODEM Legacy Model, which will enable local commissioners of services to apply the model to their own populations.

Discussion. Modelling the effects of evidence-based cost-effective interventions and making this information widely available has the potential to improve the health and quality of life both of people with dementia and their carers, while ensuring that resources are used efficiently.