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A user needs assessment to inform health information exchange design and implementation

Overview of attention for article published in BMC Medical Informatics and Decision Making, October 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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12 X users

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Title
A user needs assessment to inform health information exchange design and implementation
Published in
BMC Medical Informatics and Decision Making, October 2015
DOI 10.1186/s12911-015-0207-x
Pubmed ID
Authors

Alexandra T. Strauss, Diego A. Martinez, Andres Garcia-Arce, Stephanie Taylor, Candice Mateja, Peter J. Fabri, Jose L. Zayas-Castro

Abstract

Important barriers for widespread use of health information exchange (HIE) are usability and interface issues. However, most HIEs are implemented without performing a needs assessment with the end users, healthcare providers. We performed a user needs assessment for the process of obtaining clinical information from other health care organizations about a hospitalized patient and identified the types of information most valued for medical decision-making. Quantitative and qualitative analysis were used to evaluate the process to obtain and use outside clinical information (OI) using semi-structured interviews (16 internists), direct observation (750 h), and operational data from the electronic medical records (30,461 hospitalizations) of an internal medicine department in a public, teaching hospital in Tampa, Florida. 13.7 % of hospitalizations generate at least one request for OI. On average, the process comprised 13 steps, 6 decisions points, and 4 different participants. Physicians estimate that the average time to receive OI is 18 h. Physicians perceived that OI received is not useful 33-66 % of the time because information received is irrelevant or not timely. Technical barriers to OI use included poor accessibility and ineffective information visualization. Common problems with the process were receiving extraneous notes and the need to re-request the information. Drivers for OI use were to trend lab or imaging abnormalities, understand medical history of critically ill or hospital-to-hospital transferred patients, and assess previous echocardiograms and bacterial cultures. About 85 % of the physicians believe HIE would have a positive effect on improving healthcare delivery. Although hospitalists are challenged by a complex process to obtain OI, they recognize the value of specific information for enhancing medical decision-making. HIE systems are likely to have increased utilization and effectiveness if specific patient-level clinical information is delivered at the right time to the right users.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 129 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
Unknown 126 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 26 20%
Student > Ph. D. Student 15 12%
Student > Postgraduate 12 9%
Researcher 11 9%
Student > Bachelor 9 7%
Other 26 20%
Unknown 30 23%
Readers by discipline Count As %
Medicine and Dentistry 34 26%
Computer Science 12 9%
Engineering 10 8%
Nursing and Health Professions 9 7%
Social Sciences 8 6%
Other 19 15%
Unknown 37 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 01 December 2015.
All research outputs
#4,565,118
of 22,830,751 outputs
Outputs from BMC Medical Informatics and Decision Making
#405
of 1,989 outputs
Outputs of similar age
#61,459
of 279,097 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#8
of 36 outputs
Altmetric has tracked 22,830,751 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,989 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 79% 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 279,097 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 77% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.