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The development and appraisal of a tool designed to find patients harmed by falsely labelled, falsified (counterfeit) medicines

Overview of attention for article published in BMC Health Services Research, June 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (58th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 tweeters

Citations

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3 Dimensions

Readers on

mendeley
14 Mendeley
Title
The development and appraisal of a tool designed to find patients harmed by falsely labelled, falsified (counterfeit) medicines
Published in
BMC Health Services Research, June 2017
DOI 10.1186/s12913-017-2235-y
Pubmed ID
Authors

Marija Anđelković, Einar Björnsson, Virgilio De Bono, Nenad Dikić, Katleen Devue, Daniel Ferlin, Miroslav Hanževački, Freyja Jónsdóttir, Mkrtich Shakaryan, Sabine Walser

Abstract

Falsely labelled, falsified (counterfeit) medicines (FFCm's) are produced or distributed illegally and can harm patients. Although the occurrence of FFCm's is increasing in Europe, harm is rarely reported. The European Directorate for the Quality of Medicines & Health-Care (EDQM) has therefore coordinated the development and validation of a screening tool. The tool consists of a questionnaire referring to a watch-list of FFCm's identified in Europe, including symptoms of their use and individual risk factors, and a scoring form. To refine the questionnaire and reference method, a pilot-study was performed in 105 self-reported users of watch-list medicines. Subsequently, the tool was validated under "real-life conditions" in 371 patients in 5 ambulatory and in-patient care sites ("sub-studies"). The physicians participating in the study scored the patients and classified their risk of harm as "unlikely" or "probable" (cut-off level: presence of ≥2 of 5 risk factors). They assessed all medical records retrospectively (independent reference method) to validate the risk classification and documented their perception of the tool's value. In 3 ambulatory care sites (180 patients), the tool correctly classified 5 patients as harmed by FFCm's. The positive and negative likelihood ratios (LR+/LR-) and the discrimination power were calculated for two cut-off levels: a) 1 site (50 patients): presence of two risk factors (at 10% estimated health care system contamination with FFCm's): LR + 4.9/LR-0, post-test probability: 35%; b) 2 sites (130 patients): presence of three risk factors (at 5% estimated prevalence of use of non-prescribed medicines (FFCm's) by certain risk groups): LR + 9.7/LR-0, post-test probability: 33%. In 2 in-patient care sites (191 patients), no patient was confirmed as harmed by FFCm's. The physicians perceived the tool as valuable for finding harm, and as an information source regarding risk factors. This "decision aid" is a systematic tool which helps find in medical practice patients harmed by FFCm's. This study supports its value in ambulatory care in regions with health care system contamination and in certain risk groups. The establishment of systematic communication between authorities and the medical community concerning FFCm's, current patterns of use and case reports may sustain positive public health impacts.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters 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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 29%
Unspecified 2 14%
Student > Bachelor 2 14%
Student > Master 2 14%
Student > Ph. D. Student 1 7%
Other 3 21%
Readers by discipline Count As %
Unspecified 4 29%
Medicine and Dentistry 3 21%
Social Sciences 2 14%
Business, Management and Accounting 1 7%
Economics, Econometrics and Finance 1 7%
Other 3 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 26 June 2017.
All research outputs
#6,018,133
of 11,415,522 outputs
Outputs from BMC Health Services Research
#1,827
of 3,631 outputs
Outputs of similar age
#106,601
of 263,699 outputs
Outputs of similar age from BMC Health Services Research
#63
of 109 outputs
Altmetric has tracked 11,415,522 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,631 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 48th percentile – i.e., 48% 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 263,699 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.
We're also able to compare this research output to 109 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.