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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Checklist for Early Recognition and Treatment of Acute Illness (CERTAIN): evolution of a content management system for point-of-care clinical decision support
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, October 2016
|
| DOI | 10.1186/s12911-016-0367-3 |
| Pubmed ID | |
| Authors |
Amelia Barwise, Lisbeth Garcia-Arguello, Yue Dong, Manasi Hulyalkar, Marija Vukoja, Marcus J. Schultz, Neill K. J. Adhikari, Benjamin Bonneton, Oguz Kilickaya, Rahul Kashyap, Ognjen Gajic, Christopher N. Schmickl |
| Abstract |
The Checklist for Early Recognition and Treatment of Acute Illness (CERTAIN) is an international collaborative project with the overall objective of standardizing the approach to the evaluation and treatment of critically ill patients world-wide, in accordance with best-practice principles. One of CERTAIN's key features is clinical decision support providing point-of-care information about common acute illness syndromes, procedures, and medications in an index card format. This paper describes 1) the process of developing and validating the content for point-of-care decision support, and 2) the content management system that facilitates frequent peer-review and allows rapid updates of content across different platforms (CERTAIN software, mobile apps, pdf-booklet) and different languages. Content was created based on survey results of acute care providers and validated using an open peer-review process. Over a 3 year period, CERTAIN content expanded to include 67 syndrome cards, 30 procedure cards, and 117 medication cards. 127 (59 %) cards have been peer-reviewed so far. Initially MS Word® and Dropbox® were used to create, store, and share content for peer-review. Recently Google Docs® was used to make the peer-review process more efficient. However, neither of these approaches met our security requirements nor has the capacity to instantly update the different CERTAIN platforms. Although we were able to successfully develop and validate a large inventory of clinical decision support cards in a short period of time, commercially available software solutions for content management are suboptimal. Novel custom solutions are necessary for efficient global point of care content system management. |
X Demographics
The data shown below were collected from the profiles of 4 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 | 2 | 50% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 1% |
| Unknown | 67 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 16% |
| Researcher | 10 | 15% |
| Student > Ph. D. Student | 9 | 13% |
| Student > Postgraduate | 7 | 10% |
| Other | 7 | 10% |
| Other | 17 | 25% |
| Unknown | 7 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 23 | 34% |
| Engineering | 8 | 12% |
| Computer Science | 8 | 12% |
| Nursing and Health Professions | 5 | 7% |
| Business, Management and Accounting | 4 | 6% |
| Other | 9 | 13% |
| Unknown | 11 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 24 March 2017.
All research outputs
#12,674,864
of 22,896,955 outputs
Outputs from BMC Medical Informatics and Decision Making
#832
of 1,995 outputs
Outputs of similar age
#155,944
of 321,472 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#14
of 30 outputs
Altmetric has tracked 22,896,955 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,995 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 57% 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 321,472 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 51% of its contemporaries.
We're also able to compare this research output to 30 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 50% of its contemporaries.