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Physicians’ use of computerized clinical decision supports to improve medication management in the elderly – the Seniors Medication Alert and Review Technology intervention

Overview of attention for article published in Clinical Interventions in Aging, January 2016
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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)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

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1 news outlet
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3 X users

Citations

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24 Dimensions

Readers on

mendeley
157 Mendeley
Title
Physicians’ use of computerized clinical decision supports to improve medication management in the elderly – the Seniors Medication Alert and Review Technology intervention
Published in
Clinical Interventions in Aging, January 2016
DOI 10.2147/cia.s94126
Pubmed ID
Authors

Kannayiram Alagiakrishnan, Patricia Wilson, Cheryl A Sadowski, Darryl Rolfson, Mark Ballermann, Allen Ausford, Karla Vermeer, Kunal Mohindra, Jacques Romney, Robert S Hayward

Abstract

Elderly people (aged 65 years or more) are at increased risk of polypharmacy (five or more medications), inappropriate medication use, and associated increased health care costs. The use of clinical decision support (CDS) within an electronic medical record (EMR) could improve medication safety. Participatory action research methods were applied to preproduction design and development and postproduction optimization of an EMR-embedded CDS implementation of the Beers' Criteria for medication management and the Cockcroft-Gault formula for estimating glomerular filtration rates (GFR). The "Seniors Medication Alert and Review Technologies" (SMART) intervention was used in primary care and geriatrics specialty clinics. Passive (chart messages) and active (order-entry alerts) prompts exposed potentially inappropriate medications, decreased GFR, and the possible need for medication adjustments. Physician reactions were assessed using surveys, EMR simulations, focus groups, and semi-structured interviews. EMR audit data were used to identify eligible patient encounters, the frequency of CDS events, how alerts were managed, and when evidence links were followed. Analysis of subjective data revealed that most clinicians agreed that CDS appeared at appropriate times during patient care. Although managing alerts incurred a modest time burden, most also agreed that workflow was not disrupted. Prevalent concerns related to clinician accountability and potential liability. Approximately 36% of eligible encounters triggered at least one SMART alert, with GFR alert, and most frequent medication warnings were with hypnotics and anticholinergics. Approximately 25% of alerts were overridden and ~15% elicited an evidence check. While most SMART alerts validated clinician choices, they were received as valuable reminders for evidence-informed care and education. Data from this study may aid other attempts to implement Beers' Criteria in ambulatory care EMRs.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 157 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Spain 1 <1%
Unknown 154 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 25 16%
Researcher 21 13%
Student > Ph. D. Student 18 11%
Student > Bachelor 13 8%
Student > Postgraduate 11 7%
Other 39 25%
Unknown 30 19%
Readers by discipline Count As %
Medicine and Dentistry 47 30%
Nursing and Health Professions 17 11%
Pharmacology, Toxicology and Pharmaceutical Science 16 10%
Computer Science 8 5%
Psychology 8 5%
Other 23 15%
Unknown 38 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 11 March 2023.
All research outputs
#3,342,759
of 25,373,627 outputs
Outputs from Clinical Interventions in Aging
#357
of 1,968 outputs
Outputs of similar age
#53,984
of 399,674 outputs
Outputs of similar age from Clinical Interventions in Aging
#8
of 39 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,968 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.1. This one has done well, scoring higher than 81% 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 399,674 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 39 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.