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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A clinical decision support tool to screen health records for contraindications to stroke thrombolysis–a pilot study
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, December 2015
|
| DOI | 10.1186/s12911-015-0229-4 |
| Pubmed ID | |
| Authors |
Mu-Chien Sun, Jo-Ann Chan |
| Abstract |
The use of intravenous thrombolysis for stroke is limited by contraindications that may be difficult to identify promptly and accurately. Evidence supports the use of information technology-based clinical decision support (CDS) tools to achieve improvements in care delivery. The objective of this pilot study was to investigate the efficacy of a CDS tool to screen health records for contraindications to intravenous stroke thrombolysis. A CDS tool was developed to rapidly screen health information in seven affiliated hospitals for contraindications to stroke thrombolysis. A fixed-sequence, 2-period crossover study was conducted to test the efficacy of the CDS tool. Four mock patient records derived from the stroke registry that contained a total of nine contraindication items in two or more of the hospitals were used for testing purposes. The test patients were preset and balanced between groups with and without the CDS tool appearing six times in each group before recruiting the participating physicians. Physicians who were responsible for thrombolytic therapy and willing to sign informed consent were recruited. The participating physicians were asked to check a list of contraindications for two of the patients by using a shared electronic medical record system among the seven hospitals with and without the CDS tool. The test time and missed contraindications were recorded and analyzed statistically. A total of 14 physicians who were responsible for stroke thrombolysis were approached, and 12 signed informed consent and took the test. By using the CDS tool, the test time was reduced significantly from 14.6 ± 7.4 to 7.3 ± 5.2 min (P = 0.010). In a total of 54 contraindications, the number of missed contraindications was reduced significantly from 23 (42.6 %) to seven (13.0 %) (P = 0.001). The difference of missed contraindication number between the two groups was statistically significant either per physician or per contraindication item. By screening health records for relevant contraindications, the use of a CDS tool may reduce the time needed to review medical records and reduce the number of missed contraindications for stroke thrombolysis. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| India | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Unknown | 42 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 23% |
| Student > Master | 4 | 9% |
| Other | 3 | 7% |
| Student > Postgraduate | 3 | 7% |
| Student > Ph. D. Student | 2 | 5% |
| Other | 4 | 9% |
| Unknown | 17 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 13 | 30% |
| Psychology | 2 | 5% |
| Nursing and Health Professions | 2 | 5% |
| Decision Sciences | 2 | 5% |
| Computer Science | 1 | 2% |
| Other | 4 | 9% |
| Unknown | 19 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 18 December 2015.
All research outputs
#13,451,930
of 22,835,198 outputs
Outputs from BMC Medical Informatics and Decision Making
#986
of 1,990 outputs
Outputs of similar age
#187,807
of 389,743 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#23
of 41 outputs
Altmetric has tracked 22,835,198 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,990 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 47th percentile – i.e., 47% 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 389,743 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 50% of its contemporaries.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.