| Title |
Workflow Challenges of Enterprise Imaging: HIMSS-SIIM Collaborative White Paper
|
|---|---|
| Published in |
Journal of Digital Imaging, August 2016
|
| DOI | 10.1007/s10278-016-9897-6 |
| Pubmed ID | |
| Authors |
Alexander J. Towbin, Christopher J. Roth, Mark Bronkalla, Dawn Cram |
| Abstract |
With the advent of digital cameras, there has been an explosion in the number of medical specialties using images to diagnose or document disease and guide interventions. In many specialties, these images are not added to the patient's electronic medical record and are not distributed so that other providers caring for the patient can view them. As hospitals begin to develop enterprise imaging strategies, they have found that there are multiple challenges preventing the implementation of systems to manage image capture, image upload, and image management. This HIMSS-SIIM white paper will describe the key workflow challenges related to enterprise imaging and offer suggestions for potential solutions to these challenges. |
X Demographics
The data shown below were collected from the profiles of 11 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 | 6 | 55% |
| Canada | 1 | 9% |
| Unknown | 4 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 64% |
| Practitioners (doctors, other healthcare professionals) | 4 | 36% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Unknown | 49 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 9 | 18% |
| Researcher | 7 | 14% |
| Student > Master | 5 | 10% |
| Student > Ph. D. Student | 5 | 10% |
| Student > Doctoral Student | 3 | 6% |
| Other | 9 | 18% |
| Unknown | 12 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 22% |
| Computer Science | 6 | 12% |
| Nursing and Health Professions | 5 | 10% |
| Agricultural and Biological Sciences | 3 | 6% |
| Engineering | 3 | 6% |
| Other | 7 | 14% |
| Unknown | 15 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 24. 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 June 2019.
All research outputs
#1,400,314
of 23,577,654 outputs
Outputs from Journal of Digital Imaging
#18
of 1,087 outputs
Outputs of similar age
#27,004
of 346,435 outputs
Outputs of similar age from Journal of Digital Imaging
#1
of 12 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,087 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 98% of its peers.
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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 done particularly well, scoring higher than 91% of its contemporaries.