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Barriers to implementation of a computerized decision support system for depression: an observational report on lessons learned in "real world" clinical settings

Overview of attention for article published in BMC Medical Informatics and Decision Making, January 2009
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1 X user

Citations

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65 Dimensions

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202 Mendeley
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Title
Barriers to implementation of a computerized decision support system for depression: an observational report on lessons learned in "real world" clinical settings
Published in
BMC Medical Informatics and Decision Making, January 2009
DOI 10.1186/1472-6947-9-6
Pubmed ID
Authors

Madhukar H Trivedi, Ella J Daly, Janet K Kern, Bruce D Grannemann, Prabha Sunderajan, Cynthia A Claassen

Abstract

Despite wide promotion, clinical practice guidelines have had limited effect in changing physician behavior. Effective implementation strategies to date have included: multifaceted interventions involving audit and feedback, local consensus processes, marketing; reminder systems, either manual or computerized; and interactive educational meetings. In addition, there is now growing evidence that contextual factors affecting implementation must be addressed such as organizational support (leadership procedures and resources) for the change and strategies to implement and maintain new systems.

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 202 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 5 2%
United States 2 <1%
Canada 2 <1%
Indonesia 1 <1%
Ireland 1 <1%
Italy 1 <1%
Norway 1 <1%
Netherlands 1 <1%
Austria 1 <1%
Other 6 3%
Unknown 181 90%

Demographic breakdown

Readers by professional status Count As %
Student > Master 50 25%
Student > Ph. D. Student 32 16%
Researcher 23 11%
Student > Doctoral Student 15 7%
Student > Bachelor 14 7%
Other 42 21%
Unknown 26 13%
Readers by discipline Count As %
Computer Science 53 26%
Medicine and Dentistry 45 22%
Psychology 16 8%
Nursing and Health Professions 13 6%
Social Sciences 13 6%
Other 34 17%
Unknown 28 14%
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 13 August 2013.
All research outputs
#18,343,746
of 22,716,996 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,565
of 1,982 outputs
Outputs of similar age
#158,577
of 170,124 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#10
of 12 outputs
Altmetric has tracked 22,716,996 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,982 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 9th percentile – i.e., 9% 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 170,124 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.