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Alejandra Duenas ScHARR
Is multi-criteria decision analysis applicable to public health decision making? Alejandra Duenas ScHARR
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Outline What does NICE do? Developing NICE public health guidance
Multi-criteria decision aid methods (MCDA) MCDA in public health Future work 13/11/2018 © The University of Sheffield
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National Institute for Health and Clinical Excellence (NICE)
“NICE is an independent organisation responsible for providing national guidance on promoting good health and preventing and treating ill health. NICE produces four types of guidance: technology appraisal guidance, clinical guidelines, interventional procedure guidance and public health guidance.” 13/11/2018 © The University of Sheffield
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Examples of areas of public health
Prevention and early identification of alcohol-use disorders in adults and young people Interventions for looked after children and young people 13/11/2018 © The University of Sheffield
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Intervention/programme guidance development stages
Scoping Development Validation Publication 13/11/2018 © The University of Sheffield
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Aim of the scope clear definition of the intervention/programme
background information what to exclude settings, practitioners and public health services guidance is responsive to public health policy and practice key questions for guidance development ensure guidance can be completed 13/11/2018 © The University of Sheffield
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Development Public Health Collaborating Centre (ScHARR):
evidence reviews economic analysis stakeholders submit additional evidence (4 weeks) 13/11/2018 © The University of Sheffield
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Stakeholders draft scope synopsis of the reviews and economic analysis
draft recommendations 13/11/2018 © The University of Sheffield
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Public Health Interventions Advisory Committee
considers and interprets effectiveness and cost effectiveness evidence formulates recommendations (public health interventions): NHS local government public health in England 13/11/2018 © The University of Sheffield
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Public Health Interventions Advisory Committee
13/11/2018 © The University of Sheffield
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Programme Development Group
considers and interprets effectiveness and cost effectiveness evidence formulates recommendations (public health programmes): NHS local government public health in England 13/11/2018 © The University of Sheffield
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Programme Development Group
13/11/2018 © The University of Sheffield
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Guidance summary of evidence main conclusions overview of methodology
recommendations for practice and research synopsis of evidence (evidence reviews and economic analysis) 13/11/2018 © The University of Sheffield
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Guidance (cont) reviews of the evidence and economic analysis
field work report implementation materials 13/11/2018 © The University of Sheffield
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Multi-criteria decision aid methods
UTilities Additives DIScriminantes (UTADIS) Analytic Hierarchy Process (AHP) Outranking methods 13/11/2018 © The University of Sheffield
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Multi-criteria decision aid methods
AHP - Example 13/11/2018 © The University of Sheffield
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Multi-criteria decision aid (MCDA)
4 different decision problems: 13/11/2018 © The University of Sheffield
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MCDA description ranking sorting choice 13/11/2018
© The University of Sheffield
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MCDA description ranking sorting choice 13/11/2018
© The University of Sheffield
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MCDA description ranking sorting choice 13/11/2018
© The University of Sheffield
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MCDA description ranking sorting choice 13/11/2018
© The University of Sheffield
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Example 13/11/2018 © The University of Sheffield
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Example 13/11/2018 © The University of Sheffield
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MCDA in public health To map the multitude of components:
decision maker (DM) stakeholders objectives environment alternative courses of action public health 13/11/2018 © The University of Sheffield
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MCDA in public health Articulation of the DM's preferences considering: goals aspiration levels mechanisms for overcoming barriers and constraints 13/11/2018 © The University of Sheffield
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MCDA in public health 13/11/2018 © The University of Sheffield
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DM’s preferences Membership function of fuzzy individual schedule fitness: 13/11/2018 © The University of Sheffield
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Aspiration levels 13/11/2018 © The University of Sheffield
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Fitness function definition
Fuzzy set A = acceptable distance between the objective value and the aspiration level The membership function A represents the degree to which an achieved objective value satisfies the DM with respect to its distance from the aspiration level ALn. A ( ) 1 0.5 0.5 13/11/2018 © The University of Sheffield
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Fitness function definition
linguistically quantified statement = “most distances between the achieved objective values and the aspiration levels are acceptable” “Q ’s are A” Fitness function D is defined as: D(xv) = Truth[“Q ’s are A”] = Q( ) [0, 1] 13/11/2018 © The University of Sheffield
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Fitness function definition
Yager’s algebraic approach: For the quantifier “most”: Q( ) = 13/11/2018 © The University of Sheffield
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Fitness function definition
Find that maximises the degree of truth of the linguistically quantified fitness function: 13/11/2018 © The University of Sheffield
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Group Decision Making 13/11/2018 © The University of Sheffield
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Future work Analyse how to include uncertainty
Analyse the group accordance Incorporate MCDA to public health decision making 13/11/2018 © The University of Sheffield
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