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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Assessment of the potential impact of a reminder system on the reduction of diagnostic errors: a quasi-experimental study
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, April 2006
|
| DOI | 10.1186/1472-6947-6-22 |
| Pubmed ID | |
| Authors |
Padmanabhan Ramnarayan, Graham C Roberts, Michael Coren, Vasantha Nanduri, Amanda Tomlinson, Paul M Taylor, Jeremy C Wyatt, Joseph F Britto |
| Abstract |
Computerized decision support systems (DSS) have mainly focused on improving clinicians' diagnostic accuracy in unusual and challenging cases. However, since diagnostic omission errors may predominantly result from incomplete workup in routine clinical practice, the provision of appropriate patient- and context-specific reminders may result in greater impact on patient safety. In this experimental study, a mix of easy and difficult simulated cases were used to assess the impact of a novel diagnostic reminder system (ISABEL) on the quality of clinical decisions made by various grades of clinicians during acute assessment. |
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 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 4% |
| United States | 4 | 4% |
| Ecuador | 1 | <1% |
| Germany | 1 | <1% |
| Spain | 1 | <1% |
| Italy | 1 | <1% |
| Unknown | 96 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 17% |
| Student > Master | 15 | 14% |
| Student > Ph. D. Student | 12 | 11% |
| Other | 11 | 10% |
| Student > Doctoral Student | 7 | 6% |
| Other | 32 | 30% |
| Unknown | 13 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 47 | 44% |
| Computer Science | 11 | 10% |
| Psychology | 7 | 6% |
| Engineering | 5 | 5% |
| Social Sciences | 4 | 4% |
| Other | 16 | 15% |
| Unknown | 18 | 17% |
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 29 May 2013.
All research outputs
#6,926,349
of 22,711,242 outputs
Outputs from BMC Medical Informatics and Decision Making
#678
of 1,981 outputs
Outputs of similar age
#21,988
of 66,078 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#2
of 8 outputs
Altmetric has tracked 22,711,242 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 1,981 research outputs from this source. They receive a mean Attention Score of 4.9. 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 66,078 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 65% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.