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Implementation of a patient-facing genomic test report in the electronic health record using a web-application interface

Overview of attention for article published in BMC Medical Informatics and Decision Making, May 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

twitter
29 tweeters

Citations

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7 Dimensions

Readers on

mendeley
37 Mendeley
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Title
Implementation of a patient-facing genomic test report in the electronic health record using a web-application interface
Published in
BMC Medical Informatics and Decision Making, May 2018
DOI 10.1186/s12911-018-0614-x
Pubmed ID
Authors

Marc S. Williams, Melissa S. Kern, Virginia R. Lerch, Jonathan Billet, Janet L. Williams, Gregory J. Moore

Abstract

Genomic medicine is emerging into clinical care. Communication of genetic laboratory results to patients and providers is hampered by the complex technical nature of the laboratory reports. This can lead to confusion and misinterpretation of the results resulting in inappropriate care. Patients usually do not receive a copy of the report leading to further opportunities for miscommunication. To address these problems, interpretive reports were created using input from the intended end users, patients and providers. This paper describes the technical development and deployment of the first patient-facing genomic test report (PGR) within an electronic health record (EHR) ecosystem using a locally developed standards-based web-application interface. A patient-facing genomic test report with a companion provider report was configured for implementation within the EHR using a locally developed software platform, COMPASS™. COMPASS™ is designed to manage secure data exchange, as well as patient and provider access to patient reported data capture and clinical display tools. COMPASS™ is built using a Software as a Service (SaaS) approach which exposes an API that apps can interact with. An authoring tool was developed that allowed creation of patient-specific PGRs and the accompanying provider reports. These were converted to a format that allowed them to be presented in the patient portal and EHR respectively using the existing COMPASS™ interface thus allowing patients, caregivers and providers access to individual reports designed for the intended end user. The PGR as developed was shown to enhance patient and provider communication around genomic results. It is built on current standards but is designed to support integration with other tools and be compatible with emerging opportunities such as SMART on FHIR. This approach could be used to support genomic return of results as the tool is scalable and generalizable.

Twitter Demographics

The data shown below were collected from the profiles of 29 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 19%
Student > Ph. D. Student 5 14%
Other 5 14%
Student > Master 3 8%
Student > Postgraduate 3 8%
Other 8 22%
Unknown 6 16%
Readers by discipline Count As %
Medicine and Dentistry 5 14%
Computer Science 4 11%
Nursing and Health Professions 4 11%
Agricultural and Biological Sciences 3 8%
Biochemistry, Genetics and Molecular Biology 3 8%
Other 10 27%
Unknown 8 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 06 October 2018.
All research outputs
#1,203,981
of 14,689,555 outputs
Outputs from BMC Medical Informatics and Decision Making
#94
of 1,345 outputs
Outputs of similar age
#38,369
of 277,115 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 9 outputs
Altmetric has tracked 14,689,555 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,345 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done particularly well, scoring higher than 93% 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 277,115 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them