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Recording problems and diagnoses in clinical care: developing guidance for healthcare professionals and system designers

Overview of attention for article published in BMJ Health & Care Informatics, December 2019
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About this Attention Score

  • 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 (66th percentile)

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Title
Recording problems and diagnoses in clinical care: developing guidance for healthcare professionals and system designers
Published in
BMJ Health & Care Informatics, December 2019
DOI 10.1136/bmjhci-2019-100106
Pubmed ID
Authors

Anoop Dinesh Shah, Nicola J Quinn, Afzal Chaudhry, Ralph Sullivan, Julian Costello, Dermot O'Riordan, Jan Hoogewerf, Martin Orton, Lorraine Foley, Helene Feger, John G Williams

Abstract

Accurate recording of problems and diagnoses in health records is key to safe and effective patient care, yet it is often done poorly. Electronic health record systems vary in their functionality and ease of use, and are not optimally designed for easy recording and sharing of clinical information. There is a lack of professional consensus and guidance on how problems and diagnoses should be recorded. The Professional Record Standards Body commissioned work led by the Royal College of Physicians Health Informatics Unit to carry out a literature review, draft guidance, carry out an online consultation and round table discussion, and produce a report including recommendations for systems. A patient workshop was held to explore patient preferences for mechanisms for sharing diagnosis information between primary and secondary care. Consensus was reached among medical specialties on key elements of diagnosis recording, and draft guidance was produced ready for piloting in a variety of care settings. Patients were keen for better ways for diagnosis information to be shared. Improving the recording of diagnoses and problems will require a major effort of which the new guidance is only a part. The guidance needs to be embedded in training, and clinical systems need to have improved, standardised functionality. Front-line clinicians, specialist societies, clinical informaticians and patients need to be engaged in developing information models for diagnoses to support care and research, accessible via user-friendly interfaces.

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X Demographics

The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 13%
Student > Master 5 11%
Student > Bachelor 3 7%
Student > Ph. D. Student 3 7%
Student > Doctoral Student 2 4%
Other 6 13%
Unknown 21 46%
Readers by discipline Count As %
Medicine and Dentistry 9 20%
Nursing and Health Professions 4 9%
Computer Science 3 7%
Psychology 3 7%
Social Sciences 2 4%
Other 3 7%
Unknown 22 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 February 2020.
All research outputs
#4,941,468
of 26,314,361 outputs
Outputs from BMJ Health & Care Informatics
#123
of 511 outputs
Outputs of similar age
#107,262
of 484,821 outputs
Outputs of similar age from BMJ Health & Care Informatics
#5
of 15 outputs
Altmetric has tracked 26,314,361 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 511 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.3. This one has done well, scoring higher than 75% 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 484,821 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 15 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 66% of its contemporaries.