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Agreement between administrative data and the Resident Assessment Instrument Minimum Dataset (RAI-MDS) for medication use in long-term care facilities: a population-based study

Overview of attention for article published in BMC Geriatrics, March 2015
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  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
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Title
Agreement between administrative data and the Resident Assessment Instrument Minimum Dataset (RAI-MDS) for medication use in long-term care facilities: a population-based study
Published in
BMC Geriatrics, March 2015
DOI 10.1186/s12877-015-0023-2
Pubmed ID
Authors

Lisa M Lix, Lin Yan, David Blackburn, Nianping Hu, Verena Schneider-Lindner, Yvonne Shevchuk, Gary F Teare

Abstract

Prescription medication use, which is common among long-term care facility (LTCF) residents, is routinely used to describe quality of care and predict health outcomes. Data sources that capture medication information, which include surveys, medical charts, administrative health databases, and clinical assessment records, may not collect concordant information, which can result in comparable prevalence and effect size estimates. The purpose of this research was to estimate agreement between two population-based electronic data sources for measuring use of several medication classes among LTCF residents: outpatient prescription drug administrative data and the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0. Prescription drug and RAI-MDS data from the province of Saskatchewan, Canada (population 1.1 million) were linked for 2010/11 in this cross-sectional study. Agreement for anti-psychotic, anti-depressant, and anti-anxiety/hypnotic medication classes was examined using prevalence estimates, Cohen's κ, and positive and negative agreement. Mixed-effects logistic regression models tested resident and facility characteristics associated with disagreement. The cohort was comprised of 8,866 LTCF residents. In the RAI-MDS data, prevalence of anti-psychotics was 35.7%, while for anti-depressants it was 37.9% and for hypnotics it was 27.1%. Prevalence was similar in prescription drug data for anti-psychotics and anti-depressants, but lower for hypnotics (18.0%). Cohen's κ ranged from 0.39 to 0.85 and was highest for the first two medication classes. Diagnosis of a mood disorder and facility affiliation was associated with disagreement for hypnotics. Agreement between prescription drug administrative data and RAI-MDS assessment data was influenced by the type of medication class, as well as selected patient and facility characteristics. Researchers should carefully consider the purpose of their study, whether it is to capture medication that are dispensed or medications that are currently used by residents, when selecting a data source for research on LTCF populations.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 18%
Student > Master 5 15%
Librarian 2 6%
Other 2 6%
Student > Postgraduate 2 6%
Other 6 18%
Unknown 10 30%
Readers by discipline Count As %
Medicine and Dentistry 11 33%
Nursing and Health Professions 3 9%
Social Sciences 3 9%
Mathematics 1 3%
Psychology 1 3%
Other 3 9%
Unknown 11 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 April 2016.
All research outputs
#13,081,919
of 22,799,071 outputs
Outputs from BMC Geriatrics
#1,913
of 3,180 outputs
Outputs of similar age
#119,740
of 259,187 outputs
Outputs of similar age from BMC Geriatrics
#25
of 36 outputs
Altmetric has tracked 22,799,071 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,180 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.5. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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 259,187 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% 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 is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.