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Methods to estimate access to care and the effect of interventions on the outcomes of congenital disorders

Overview of attention for article published in Journal of Community Genetics, March 2018
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Title
Methods to estimate access to care and the effect of interventions on the outcomes of congenital disorders
Published in
Journal of Community Genetics, March 2018
DOI 10.1007/s12687-018-0359-3
Pubmed ID
Authors

Hannah Blencowe, Sowmiya Moorthie, Matthew W. Darlison, Stephen Gibbons, Bernadette Modell, Congenital Disorders Expert Group

Abstract

In the absence of intervention, early-onset congenital disorders lead to pregnancy loss, early death, or disability. Currently, lack of epidemiological data from many settings limits the understanding of the burden of these conditions, thus impeding health planning, policy-making, and commensurate resource allocation. The Modell Global Database of Congenital Disorders (MGDb) seeks to meet this need by combining general biological principles with observational and demographic data, to generate estimates of the burden of congenital disorders. A range of interventions along the life course can modify adverse outcomes associated with congenital disorders. Hence, access to and quality of services available for the prevention and care of congenital disorders affects both their birth prevalence and the outcomes for affected individuals. Information on this is therefore important to enable burden estimates for settings with limited observational data, but is lacking from many settings. This paper, the third in this special issue on methods used in the MGDb for estimating the global burden of congenital disorders, describes key interventions that impact on outcomes of congenital disorders and methods used to estimate their coverage where empirical data are not available.

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Mendeley readers

Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 18%
Student > Bachelor 7 14%
Researcher 7 14%
Professor 4 8%
Student > Doctoral Student 4 8%
Other 4 8%
Unknown 15 30%
Readers by discipline Count As %
Medicine and Dentistry 15 30%
Nursing and Health Professions 8 16%
Biochemistry, Genetics and Molecular Biology 4 8%
Psychology 2 4%
Economics, Econometrics and Finance 2 4%
Other 4 8%
Unknown 15 30%
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 18 July 2018.
All research outputs
#20,485,225
of 23,047,237 outputs
Outputs from Journal of Community Genetics
#337
of 371 outputs
Outputs of similar age
#317,138
of 359,629 outputs
Outputs of similar age from Journal of Community Genetics
#7
of 9 outputs
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So far Altmetric has tracked 371 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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