↓ Skip to main content

Multi-Criteria Clinical Decision Support

Overview of attention for article published in The Patient - Patient-Centered Outcomes Research, August 2012
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

policy
1 policy source
patent
2 patents
facebook
1 Facebook page

Citations

dimensions_citation
148 Dimensions

Readers on

mendeley
119 Mendeley
Title
Multi-Criteria Clinical Decision Support
Published in
The Patient - Patient-Centered Outcomes Research, August 2012
DOI 10.2165/11539470-000000000-00000
Pubmed ID
Authors

James G. Dolan

Abstract

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 119 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Netherlands 1 <1%
Greece 1 <1%
Unknown 115 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 16%
Researcher 18 15%
Student > Master 16 13%
Other 7 6%
Student > Postgraduate 7 6%
Other 22 18%
Unknown 30 25%
Readers by discipline Count As %
Medicine and Dentistry 26 22%
Computer Science 9 8%
Engineering 7 6%
Nursing and Health Professions 6 5%
Social Sciences 6 5%
Other 34 29%
Unknown 31 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 18 April 2016.
All research outputs
#5,475,550
of 25,856,713 outputs
Outputs from The Patient - Patient-Centered Outcomes Research
#183
of 598 outputs
Outputs of similar age
#38,141
of 187,638 outputs
Outputs of similar age from The Patient - Patient-Centered Outcomes Research
#8
of 39 outputs
Altmetric has tracked 25,856,713 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 598 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has gotten more attention than average, scoring higher than 69% 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 187,638 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 79% of its contemporaries.
We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.