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Addressing preference heterogeneity in public health policy by combining Cluster Analysis and Multi-Criteria Decision Analysis: Proof of Method

Overview of attention for article published in Health Economics Review, May 2015
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Title
Addressing preference heterogeneity in public health policy by combining Cluster Analysis and Multi-Criteria Decision Analysis: Proof of Method
Published in
Health Economics Review, May 2015
DOI 10.1186/s13561-015-0048-4
Pubmed ID
Authors

Mette Kjer Kaltoft, Robin Turner, Michelle Cunich, Glenn Salkeld, Jesper Bo Nielsen, Jack Dowie

Abstract

The use of subgroups based on biological-clinical and socio-demographic variables to deal with population heterogeneity is well-established in public policy. The use of subgroups based on preferences is rare, except when religion based, and controversial. If it were decided to treat subgroup preferences as valid determinants of public policy, a transparent analytical procedure is needed. In this proof of method study we show how public preferences could be incorporated into policy decisions in a way that respects both the multi-criterial nature of those decisions, and the heterogeneity of the population in relation to the importance assigned to relevant criteria. It involves combining Cluster Analysis (CA), to generate the subgroup sets of preferences, with Multi-Criteria Decision Analysis (MCDA), to provide the policy framework into which the clustered preferences are entered. We employ three techniques of CA to demonstrate that not only do different techniques produce different clusters, but that choosing among techniques (as well as developing the MCDA structure) is an important task to be undertaken in implementing the approach outlined in any specific policy context. Data for the illustrative, not substantive, application are from a Randomized Controlled Trial of online decision aids for Australian men aged 40-69 years considering Prostate-specific Antigen testing for prostate cancer. We show that such analyses can provide policy-makers with insights into the criterion-specific needs of different subgroups. Implementing CA and MCDA in combination to assist in the development of policies on important health and community issues such as drug coverage, reimbursement, and screening programs, poses major challenges -conceptual, methodological, ethical-political, and practical - but most are exposed by the techniques, not created by them.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Netherlands 1 1%
Unknown 81 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 16%
Student > Master 12 14%
Student > Ph. D. Student 8 10%
Student > Bachelor 8 10%
Other 6 7%
Other 14 17%
Unknown 22 27%
Readers by discipline Count As %
Medicine and Dentistry 12 14%
Nursing and Health Professions 8 10%
Agricultural and Biological Sciences 6 7%
Economics, Econometrics and Finance 6 7%
Pharmacology, Toxicology and Pharmaceutical Science 6 7%
Other 19 23%
Unknown 26 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 May 2015.
All research outputs
#18,409,030
of 22,803,211 outputs
Outputs from Health Economics Review
#333
of 429 outputs
Outputs of similar age
#192,004
of 264,461 outputs
Outputs of similar age from Health Economics Review
#8
of 9 outputs
Altmetric has tracked 22,803,211 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
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