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Strengthening the evidence-base of integrated care for people with multi-morbidity in Europe using Multi-Criteria Decision Analysis (MCDA)

Overview of attention for article published in BMC Health Services Research, July 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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1 blog
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9 X users
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1 Facebook page

Citations

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47 Dimensions

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176 Mendeley
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Title
Strengthening the evidence-base of integrated care for people with multi-morbidity in Europe using Multi-Criteria Decision Analysis (MCDA)
Published in
BMC Health Services Research, July 2018
DOI 10.1186/s12913-018-3367-4
Pubmed ID
Authors

Maureen Rutten-van Mölken, Fenna Leijten, Maaike Hoedemakers, Apostolos Tsiachristas, Nick Verbeek, Milad Karimi, Roland Bal, Antoinette de Bont, Kamrul Islam, Jan Erik Askildsen, Thomas Czypionka, Markus Kraus, Mirjana Huic, János György Pitter, Verena Vogt, Jonathan Stokes, Erik Baltaxe, on behalf of the SELFIE consortium

Abstract

Evaluation of integrated care programmes for individuals with multi-morbidity requires a broader evaluation framework and a broader definition of added value than is common in cost-utility analysis. This is possible through the use of Multi-Criteria Decision Analysis (MCDA). This paper presents the seven steps of an MCDA to evaluate 17 different integrated care programmes for individuals with multi-morbidity in 8 European countries participating in the 4-year, EU-funded SELFIE project. In step one, qualitative research was undertaken to better understand the decision-context of these programmes. The programmes faced decisions related to their sustainability in terms of reimbursement, continuation, extension, and/or wider implementation. In step two, a uniform set of decision criteria was defined in terms of outcomes measured across the 17 programmes: physical functioning, psychological well-being, social relationships and participation, enjoyment of life, resilience, person-centeredness, continuity of care, and total health and social care costs. These were supplemented by programme-type specific outcomes. Step three presents the quasi-experimental studies designed to measure the performance of the programmes on the decision criteria. Step four gives details of the methods (Discrete Choice Experiment, Swing Weighting) to determine the relative importance of the decision criteria among five stakeholder groups per country. An example in step five illustrates the value-based method of MCDA by which the performance of the programmes on each decision criterion is combined with the weight of the respective criterion to derive an overall value score. Step six describes how we deal with uncertainty and introduces the Conditional Multi-Attribute Acceptability Curve. Step seven addresses the interpretation of results in stakeholder workshops. By discussing our solutions to the challenges involved in creating a uniform MCDA approach for the evaluation of different programmes, this paper provides guidance to future evaluations and stimulates debate on how to evaluate integrated care for multi-morbidity.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 176 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 176 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 16%
Researcher 25 14%
Student > Master 22 13%
Other 12 7%
Student > Bachelor 12 7%
Other 26 15%
Unknown 51 29%
Readers by discipline Count As %
Medicine and Dentistry 37 21%
Nursing and Health Professions 23 13%
Business, Management and Accounting 12 7%
Social Sciences 11 6%
Engineering 7 4%
Other 31 18%
Unknown 55 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 23 February 2020.
All research outputs
#2,504,663
of 23,798,792 outputs
Outputs from BMC Health Services Research
#1,034
of 7,917 outputs
Outputs of similar age
#51,962
of 331,031 outputs
Outputs of similar age from BMC Health Services Research
#45
of 203 outputs
Altmetric has tracked 23,798,792 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,917 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 331,031 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 203 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.