↓ Skip to main content

Identifying patients with chronic conditions using pharmacy data in Switzerland: an updated mapping approach to the classification of medications

Overview of attention for article published in BMC Public Health, October 2013
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
153 Dimensions

Readers on

mendeley
128 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Identifying patients with chronic conditions using pharmacy data in Switzerland: an updated mapping approach to the classification of medications
Published in
BMC Public Health, October 2013
DOI 10.1186/1471-2458-13-1030
Pubmed ID
Authors

Carola A Huber, Thomas D Szucs, Roland Rapold, Oliver Reich

Abstract

Quantifying population health is important for public health policy. Since national disease registers recording clinical diagnoses are often not available, pharmacy data were frequently used to identify chronic conditions (CCs) in populations. However, most approaches mapping prescribed drugs to CCs are outdated and unambiguous. The aim of this study was to provide an improved and updated mapping approach to the classification of medications. Furthermore, we aimed to give an overview of the proportions of patients with CCs in Switzerland using this new mapping approach.

X Demographics

X Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
United States 1 <1%
Denmark 1 <1%
Australia 1 <1%
Unknown 124 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 22%
Student > Ph. D. Student 20 16%
Student > Master 12 9%
Other 8 6%
Student > Postgraduate 7 5%
Other 25 20%
Unknown 28 22%
Readers by discipline Count As %
Medicine and Dentistry 39 30%
Economics, Econometrics and Finance 9 7%
Nursing and Health Professions 9 7%
Social Sciences 9 7%
Psychology 6 5%
Other 23 18%
Unknown 33 26%
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 20 November 2013.
All research outputs
#15,285,728
of 22,731,677 outputs
Outputs from BMC Public Health
#11,291
of 14,808 outputs
Outputs of similar age
#130,711
of 212,652 outputs
Outputs of similar age from BMC Public Health
#241
of 294 outputs
Altmetric has tracked 22,731,677 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,808 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.9. This one is in the 16th percentile – i.e., 16% 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 212,652 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 294 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.