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Applying systems biology to biomedical research and health care: a précising definition of systems medicine

Overview of attention for article published in BMC Health Services Research, November 2017
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1 tweeter

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21 Dimensions

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56 Mendeley
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Title
Applying systems biology to biomedical research and health care: a précising definition of systems medicine
Published in
BMC Health Services Research, November 2017
DOI 10.1186/s12913-017-2688-z
Pubmed ID
Authors

Sebastian Schleidgen, Sandra Fernau, Henrike Fleischer, Christoph Schickhardt, Ann-Kristin Oßa, Eva C. Winkler

Abstract

Systems medicine has become a key word in biomedical research. Although it is often referred to as P4-(predictive, preventive, personalized and participatory)-medicine, it still lacks a clear definition and is open to interpretation. This conceptual lack of clarity complicates the scientific and public discourse on chances, risks and limits of Systems Medicine and may lead to unfounded hopes. Against this background, our goal was to develop a sufficiently precise and widely acceptable definition of Systems Medicine. In a first step, PubMed was searched using the keyword "systems medicine". A data extraction tabloid was developed putting forward a means/ends-division. Full-texts of articles containing Systems Medicine in title or abstract were screened for definitions. Definitions were extracted; their semantic elements were assigned as either means or ends. To reduce complexity of the resulting list, summary categories were developed inductively. In a second step, we applied six criteria for adequate definitions (necessity, non-circularity, non-redundancy, consistency, non-vagueness, and coherence) to these categories to derive a so-called précising definition of Systems Medicine. We identified 185 articles containing the term Systems Medicine in title or abstract. 67 contained at least one definition of Systems Medicine. In 98 definitions, we found 114 means and 132 ends. From these we derived the précising definition: Systems Medicine is an approach seeking to improve medical research (i.e. the understanding of complex processes occurring in diseases, pathologies and health states as well as innovative approaches to drug discovery) and health care (i.e. prevention, prediction, diagnosis and treatment) through stratification by means of Systems Biology (i.e. data integration, modeling, experimentation and bioinformatics). Our study also revealed the visionary character of Systems Medicine. Our insights, on the one hand, allow for a realistic identification of actual ethical as well as legal issues arising in the context of Systems Medicine and, in consequence, for a realistic debate of questions concerning its matter and (future) handling. On the other hand, they help avoiding unfounded hopes and unrealistic expectations. This especially holds for goals like improving patient participation which are intensely debated in the context of Systems Medicine, however not implied in the concept.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 23%
Student > Master 9 16%
Student > Ph. D. Student 8 14%
Student > Bachelor 5 9%
Other 4 7%
Other 5 9%
Unknown 12 21%
Readers by discipline Count As %
Medicine and Dentistry 11 20%
Biochemistry, Genetics and Molecular Biology 5 9%
Agricultural and Biological Sciences 3 5%
Computer Science 3 5%
Social Sciences 3 5%
Other 15 27%
Unknown 16 29%

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 22 November 2017.
All research outputs
#7,609,604
of 12,177,594 outputs
Outputs from BMC Health Services Research
#2,780
of 3,969 outputs
Outputs of similar age
#187,303
of 336,537 outputs
Outputs of similar age from BMC Health Services Research
#112
of 194 outputs
Altmetric has tracked 12,177,594 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,969 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 19th percentile – i.e., 19% 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 336,537 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 194 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.