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Multimorbidity and Evidence Generation

Overview of attention for article published in Journal of General Internal Medicine, January 2014
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Title
Multimorbidity and Evidence Generation
Published in
Journal of General Internal Medicine, January 2014
DOI 10.1007/s11606-013-2660-5
Pubmed ID
Authors

Carlos O. Weiss, Ravi Varadhan, Milo A. Puhan, Andrew Vickers, Karen Bandeen-Roche, Cynthia M. Boyd, David M. Kent

Abstract

Most people with a chronic disease actually have more than one, a condition known as multimorbidity. Despite this, the evidence base to prevent adverse disease outcomes has taken a disease-specific approach. Drawing on a conference, Improving Guidelines for Multimorbid Patients, the goal of this paper is to identify challenges to the generation of evidence to support the care of people with multimorbidity and to make recommendations for improvement. We identified three broad categories of challenges: 1) challenges to defining and measuring multimorbidity; 2) challenges related to the effects of multimorbidity on study design, implementation and analysis; and 3) challenges inherent in studying heterogeneity of treatment effects in patients with differing comorbid conditions. We propose a set of recommendations for consideration by investigators and others (reviewers, editors, funding agencies, policymaking organizations) involved in the creation of evidence for this common type of person that address each of these challenges. The recommendations reflect a general approach that emphasizes broader inclusion (recruitment and retention) of patients with multimorbidity, coupled with more rigorous efforts to measure comorbidity and comorbidity burden and the influence of multimorbidity on outcomes and the effects of therapy. More rigorous examination of heterogeneity of treatment effects requires careful attention to prioritizing the most important comorbid-related questions, and also requires studies that provide greater statistical power than conventional trials have provided. Relatively modest changes in the orientation of current research along these lines can be helpful in pointing to and partially addressing selected knowledge gaps. However, producing a robust evidence base to support patient-centered decision making in complex individuals with multimorbidity, exposed to many different combinations of potentially interacting factors that can modify the risks and benefits of therapies, is likely to require a clinical research enterprise fundamentally restructured to be more fully integrated with routine clinical practice.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
Brazil 1 <1%
Italy 1 <1%
Spain 1 <1%
United Kingdom 1 <1%
Unknown 120 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 15%
Researcher 15 12%
Student > Master 11 9%
Student > Postgraduate 9 7%
Professor 9 7%
Other 40 31%
Unknown 24 19%
Readers by discipline Count As %
Medicine and Dentistry 61 48%
Nursing and Health Professions 8 6%
Social Sciences 6 5%
Business, Management and Accounting 3 2%
Agricultural and Biological Sciences 3 2%
Other 19 15%
Unknown 27 21%
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 March 2014.
All research outputs
#19,440,618
of 23,911,072 outputs
Outputs from Journal of General Internal Medicine
#6,622
of 7,806 outputs
Outputs of similar age
#235,963
of 312,506 outputs
Outputs of similar age from Journal of General Internal Medicine
#77
of 104 outputs
Altmetric has tracked 23,911,072 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,806 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.8. This one is in the 7th percentile – i.e., 7% of its peers scored the same or lower than it.
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 312,506 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 104 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.