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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, February 2009
|
| DOI | 10.1186/1472-6947-9-11 |
| Pubmed ID | |
| Authors |
Brent Mollon, Jaron JR Chong, Anne M Holbrook, Melani Sung, Lehana Thabane, Gary Foster |
| Abstract |
Computerized decision support systems (CDSS) are believed to have the potential to improve the quality of health care delivery, although results from high quality studies have been mixed. We conducted a systematic review to evaluate whether certain features of prescribing decision support systems (RxCDSS) predict successful implementation, change in provider behaviour, and change in patient outcomes. |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 225 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 10 | 4% |
| United Kingdom | 6 | 3% |
| Canada | 2 | <1% |
| Germany | 2 | <1% |
| India | 2 | <1% |
| Spain | 2 | <1% |
| Norway | 1 | <1% |
| Saudi Arabia | 1 | <1% |
| Portugal | 1 | <1% |
| Other | 2 | <1% |
| Unknown | 196 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 60 | 27% |
| Researcher | 32 | 14% |
| Student > Ph. D. Student | 29 | 13% |
| Student > Postgraduate | 19 | 8% |
| Other | 17 | 8% |
| Other | 52 | 23% |
| Unknown | 16 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 92 | 41% |
| Computer Science | 43 | 19% |
| Business, Management and Accounting | 17 | 8% |
| Nursing and Health Professions | 11 | 5% |
| Social Sciences | 9 | 4% |
| Other | 25 | 11% |
| Unknown | 28 | 12% |
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 26 March 2018.
All research outputs
#7,398,753
of 23,885,338 outputs
Outputs from BMC Medical Informatics and Decision Making
#715
of 2,048 outputs
Outputs of similar age
#49,030
of 177,782 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#5
of 12 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 2,048 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 64% 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 177,782 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 12 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 58% of its contemporaries.