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Factors influencing rheumatologists’ prescription of biological treatment in rheumatoid arthritis: an interview study

Overview of attention for article published in Implementation Science, October 2014
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  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

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6 X users

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Title
Factors influencing rheumatologists’ prescription of biological treatment in rheumatoid arthritis: an interview study
Published in
Implementation Science, October 2014
DOI 10.1186/s13012-014-0153-5
Pubmed ID
Authors

Almina Kalkan, Kerstin Roback, Eva Hallert, Per Carlsson

Abstract

BackgroundThe introduction of biological drugs involved a fundamental change in the treatment of rheumatoid arthritis (RA). The extent to which biological drugs are prescribed to RA patients in different regions in Sweden varies greatly. Previous research has indicated that differences in health care practice at the regional level might obscure differences at the individual level. The objective of this study is to explore what influences individual rheumatologists¿ decisions when prescribing biological drugs.MethodSemi-structured interviews, utilizing closed- and open-ended questions, were conducted with senior rheumatologists, selected through a mix of random and purposive sampling. The interview questions consisted of two parts, with a ¿parallel mixed method¿ approach. In the first and main part, open-ended exploratory questions were posed about factors influencing prescription. In the second part, the rheumatologists were asked to rate predefined factors that might influence their prescription decisions. The Consolidated Framework for Implementation Research (CFIR) was used as a conceptual framework for data collection and analysis.ResultsTwenty-six rheumatologists were interviewed. A constellation of various factors and their interaction influenced rheumatologists¿ prescribing decisions, including the individual rheumatologist¿s experiences and perceptions of the evidence, the structure of the department including responsibility for costs, peer pressure, political and administrative influences, and participation in clinical trials. The patient as an actor emerged as an important factor. Hence, factors both at organizational and individual levels influenced the prescribing of biological drugs. The factors should not be seen as individual influences but were described as influencing prescription in an interactive, nonlinear way.ConclusionsPotential factors explaining differences in prescription practice are experience and perception of the evidence on the individual level and the structure of the department and participation in clinical trials on the organizational level. The influence of patient attitudes and preferences and interpretation of scientific evidence seemed to be somewhat contradictory in the qualitative responses as compared to the quantitative rating, and this needs further exploration. An implication of the present study is that in addition to scientific knowledge, attempts to influence prescription behavior need to be multifactorial and account for interactions of factors between different actors.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Unknown 112 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 17%
Researcher 14 12%
Student > Ph. D. Student 14 12%
Student > Bachelor 10 9%
Student > Doctoral Student 8 7%
Other 22 19%
Unknown 26 23%
Readers by discipline Count As %
Medicine and Dentistry 31 27%
Nursing and Health Professions 9 8%
Pharmacology, Toxicology and Pharmaceutical Science 9 8%
Psychology 8 7%
Social Sciences 5 4%
Other 17 15%
Unknown 34 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 16 July 2015.
All research outputs
#6,407,957
of 22,766,595 outputs
Outputs from Implementation Science
#1,111
of 1,721 outputs
Outputs of similar age
#69,446
of 256,089 outputs
Outputs of similar age from Implementation Science
#28
of 60 outputs
Altmetric has tracked 22,766,595 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 1,721 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one is in the 34th percentile – i.e., 34% 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 256,089 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 71% of its contemporaries.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.