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Cognitive workload changes for nurses transitioning from a legacy system with paper documentation to a commercial electronic health record

Overview of attention for article published in International Journal of Medical Informatics, July 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#22 of 1,368)
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

policy
1 policy source
twitter
45 tweeters
patent
1 patent
wikipedia
2 Wikipedia pages
googleplus
1 Google+ user

Citations

dimensions_citation
73 Dimensions

Readers on

mendeley
227 Mendeley
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Title
Cognitive workload changes for nurses transitioning from a legacy system with paper documentation to a commercial electronic health record
Published in
International Journal of Medical Informatics, July 2015
DOI 10.1016/j.ijmedinf.2015.03.003
Pubmed ID
Authors

Lacey Colligan, Henry W.W. Potts, Chelsea T. Finn, Robert A. Sinkin

Abstract

Healthcare institutions worldwide are moving to electronic health records (EHRs). These transitions are particularly numerous in the US where healthcare systems are purchasing and implementing commercial EHRs to fulfill federal requirements. Despite the central role of EHRs to workflow, the cognitive impact of these transitions on the workforce has not been widely studied. This study assesses the changes in cognitive workload among pediatric nurses during data entry and retrieval tasks during transition from a hybrid electronic and paper information system to a commercial EHR. Baseline demographics and computer attitude and skills scores were obtained from 74 pediatric nurses in two wards. They also completed an established and validated instrument, the NASA-TLX, that is designed to measure cognitive workload; this instrument was used to evaluate cognitive workload of data entry and retrieval. The NASA-TLX was administered at baseline (pre-implementation), 1, 5 and 10 shifts and 4 months post-implementation of the new EHR. Most nurse participants experienced significant increases of cognitive workload at 1 and 5 shifts after "go-live". These increases abated at differing rates predicted by participants' computer attitudes scores (p=0.01). There is substantially increased cognitive workload for nurses during the early phases (1-5 shifts) of EHR transitions. Health systems should anticipate variability across workers adapting to "meaningful use" EHRs. "One-size-fits-all" training strategies may not be suitable and longer periods of technical support may be necessary for some workers.

Twitter Demographics

The data shown below were collected from the profiles of 45 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 227 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 1%
United States 2 <1%
Ireland 1 <1%
Canada 1 <1%
Unknown 220 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 63 28%
Student > Ph. D. Student 30 13%
Student > Bachelor 22 10%
Researcher 22 10%
Student > Doctoral Student 16 7%
Other 46 20%
Unknown 28 12%
Readers by discipline Count As %
Nursing and Health Professions 41 18%
Computer Science 35 15%
Medicine and Dentistry 32 14%
Engineering 24 11%
Business, Management and Accounting 11 5%
Other 40 18%
Unknown 44 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 37. 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 08 March 2019.
All research outputs
#667,242
of 17,388,379 outputs
Outputs from International Journal of Medical Informatics
#22
of 1,368 outputs
Outputs of similar age
#11,319
of 231,038 outputs
Outputs of similar age from International Journal of Medical Informatics
#1
of 19 outputs
Altmetric has tracked 17,388,379 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,368 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 98% 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 231,038 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 19 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 99% of its contemporaries.