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Improving specialist drug prescribing in primary care using task and error analysis: an observational study

Overview of attention for article published in British Journal of General Practice, February 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

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Title
Improving specialist drug prescribing in primary care using task and error analysis: an observational study
Published in
British Journal of General Practice, February 2017
DOI 10.3399/bjgp17x689389
Pubmed ID
Authors

Narinder Chana, Talya Porat, Cate Whittlesea, Brendan Delaney

Abstract

Electronic prescribing has benefited from computerised clinical decision support systems (CDSSs); however, no published studies have evaluated the potential for a CDSS to support GPs in prescribing specialist drugs. To identify potential weaknesses and errors in the existing process of prescribing specialist drugs that could be addressed in the development of a CDSS. Semi-structured interviews with key informants followed by an observational study involving GPs in the UK. Twelve key informants were interviewed to investigate the use of CDSSs in the UK. Nine GPs were observed while performing case scenarios depicting requests from hospitals or patients to prescribe a specialist drug. Activity diagrams, hierarchical task analysis, and systematic human error reduction and prediction approach analyses were performed. The current process of prescribing specialist drugs by GPs is prone to error. Errors of omission due to lack of information were the most common errors, which could potentially result in a GP prescribing a specialist drug that should only be prescribed in hospitals, or prescribing a specialist drug without reference to a shared care protocol. Half of all possible errors in the prescribing process had a high probability of occurrence. A CDSS supporting GPs during the process of prescribing specialist drugs is needed. This could, first, support the decision making of whether or not to undertake prescribing, and, second, provide drug-specific parameters linked to shared care protocols, which could reduce the errors identified and increase patient safety.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 X users 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 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 79 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 24%
Researcher 9 11%
Student > Doctoral Student 8 10%
Student > Postgraduate 7 9%
Student > Bachelor 5 6%
Other 13 16%
Unknown 18 23%
Readers by discipline Count As %
Medicine and Dentistry 23 29%
Nursing and Health Professions 10 13%
Pharmacology, Toxicology and Pharmaceutical Science 7 9%
Engineering 4 5%
Psychology 4 5%
Other 12 15%
Unknown 19 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 March 2017.
All research outputs
#4,208,412
of 22,953,506 outputs
Outputs from British Journal of General Practice
#1,638
of 4,294 outputs
Outputs of similar age
#88,592
of 426,820 outputs
Outputs of similar age from British Journal of General Practice
#38
of 90 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,294 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.5. This one has gotten more attention than average, scoring higher than 61% of its peers.
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 426,820 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 90 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 56% of its contemporaries.