↓ Skip to main content

Medication review algorithm

Overview of attention for article published in Geriatrics & Gerontology International, September 2015
Altmetric Badge

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)
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

Mentioned by

twitter
11 X users

Readers on

mendeley
161 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Medication review algorithm
Published in
Geriatrics & Gerontology International, September 2015
DOI 10.1111/ggi.12589
Pubmed ID
Authors

Arjun Poudel, Anna Ballokova, Ruth E Hubbard, Leonard C Gray, Charles A Mitchell, Lisa M Nissen, Ian A Scott

Abstract

Frail older people typically suffer several chronic diseases, receive multiple medications and are more likely to be institutionalized in residential aged care facilities. In such patients, optimizing prescribing and avoiding use of high-risk medications might prevent adverse events. The present study aimed to develop a pragmatic, easily applied algorithm for medication review to help clinicians identify and discontinue potentially inappropriate high-risk medications. The literature was searched for robust evidence of the association of adverse effects related to potentially inappropriate medications in older patients to identify high-risk medications. Prior research into the cessation of potentially inappropriate medications in older patients in different settings was synthesized into a four-step algorithm for incorporation into clinical assessment protocols for patients, particularly those in residential aged care facilities. The algorithm comprises several steps leading to individualized prescribing recommendations: (i) identify a high-risk medication; (ii) ascertain the current indications for the medication and assess their validity; (iii) assess if the drug is providing ongoing symptomatic benefit; and (iv) consider withdrawing, altering or continuing medications. Decision support resources were developed to complement the algorithm in ensuring a systematic and patient-centered approach to medication discontinuation. These include a comprehensive list of high-risk medications and the reasons for inappropriateness, lists of alternative treatments, and suggested medication withdrawal protocols. The algorithm captures a range of different clinical scenarios in relation to potentially inappropriate medications, and offers an evidence-based approach to identifying and, if appropriate, discontinuing such medications. Studies are required to evaluate algorithm effects on prescribing decisions and patient outcomes. Geriatr Gerontol Int 2015; ●●: ●●-●●.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 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 161 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 161 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 16%
Researcher 23 14%
Student > Master 20 12%
Student > Bachelor 15 9%
Other 10 6%
Other 25 16%
Unknown 43 27%
Readers by discipline Count As %
Medicine and Dentistry 35 22%
Pharmacology, Toxicology and Pharmaceutical Science 32 20%
Nursing and Health Professions 19 12%
Computer Science 4 2%
Engineering 4 2%
Other 16 10%
Unknown 51 32%
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 28 June 2017.
All research outputs
#5,405,755
of 25,374,917 outputs
Outputs from Geriatrics & Gerontology International
#334
of 1,362 outputs
Outputs of similar age
#63,157
of 277,000 outputs
Outputs of similar age from Geriatrics & Gerontology International
#10
of 28 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,362 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.9. 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 277,000 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 28 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 64% of its contemporaries.