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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Organization-wide adoption of computerized provider order entry systems: a study based on diffusion of innovations theory
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, December 2009
|
| DOI | 10.1186/1472-6947-9-52 |
| Pubmed ID | |
| Authors |
Bahlol Rahimi, Toomas Timpka, Vivian Vimarlund, Srinivas Uppugunduri, Mikael Svensson |
| Abstract |
Computerized provider order entry (CPOE) systems have been introduced to reduce medication errors, increase safety, improve work-flow efficiency, and increase medical service quality at the moment of prescription. Making the impact of CPOE systems more observable may facilitate their adoption by users. We set out to examine factors associated with the adoption of a CPOE system for inter-organizational and intra-organizational care. |
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 173 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 3 | 2% |
| United States | 3 | 2% |
| France | 1 | <1% |
| Italy | 1 | <1% |
| United Kingdom | 1 | <1% |
| Malaysia | 1 | <1% |
| Argentina | 1 | <1% |
| Indonesia | 1 | <1% |
| Spain | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 159 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 41 | 24% |
| Student > Ph. D. Student | 36 | 21% |
| Researcher | 14 | 8% |
| Other | 10 | 6% |
| Professor > Associate Professor | 10 | 6% |
| Other | 40 | 23% |
| Unknown | 22 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 46 | 27% |
| Business, Management and Accounting | 25 | 14% |
| Computer Science | 23 | 13% |
| Nursing and Health Professions | 15 | 9% |
| Social Sciences | 13 | 8% |
| Other | 28 | 16% |
| Unknown | 23 | 13% |
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 15 September 2013.
All research outputs
#18,347,414
of 22,721,584 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,565
of 1,982 outputs
Outputs of similar age
#149,763
of 163,272 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#5
of 7 outputs
Altmetric has tracked 22,721,584 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 163,272 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.