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Failure to refill essential prescription medications for asthma among pediatric Medicaid beneficiaries with persistent asthma

Overview of attention for article published in Patient preference and adherence, January 2013
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Mentioned by

twitter
1 tweeter

Citations

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9 Dimensions

Readers on

mendeley
16 Mendeley
citeulike
1 CiteULike
Title
Failure to refill essential prescription medications for asthma among pediatric Medicaid beneficiaries with persistent asthma
Published in
Patient preference and adherence, January 2013
DOI 10.2147/ppa.s37811
Pubmed ID
Authors

Varun Vaidya, Gupte, Rajesh Balkrishnan

Abstract

The problem of patients not taking medications as prescribed, also known as "lack of medication adherence," is widely discussed as an issue related to suboptimal outcomes and excess health care expenditure. Although medication adherence is defined as patients not taking medications as prescribed, there are two elements to it: first, those who fail to follow the medication regimen by skipping a dose or not following the instructions, resulting in poor adherence with prescribed medicines; and, second, the patient who does not take the medication at all or stops after the initial fill. The existing literature contains a lot of studies on the first element, but very little is known about those who stop taking their medication after the initial fill or do not take it at all. In this study, our focus is on identifying patients who fail to refill a prescription for essential medicines, such as asthma-controlling drugs. Using Medicaid claims datasets, this study analyzed a pediatric population diagnosed with persistent asthma that discontinued an essential controlling medication after the initial fill. We found that more than half of this population did not continue their medication after the first fill. While there might be many reasons behind the failure to refill such medications, our data indicate that race/ethnicity, comorbid illness, and type of Medicaid plan are potentially associated with such behavior. Future research is warranted to understand this issue further and identify specific factors causing such behavior, such that strategies may be formulated by which poor adherence can be minimized.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 25%
Researcher 3 19%
Student > Doctoral Student 2 13%
Other 1 6%
Professor 1 6%
Other 4 25%
Unknown 1 6%
Readers by discipline Count As %
Medicine and Dentistry 6 38%
Pharmacology, Toxicology and Pharmaceutical Science 3 19%
Nursing and Health Professions 1 6%
Business, Management and Accounting 1 6%
Agricultural and Biological Sciences 1 6%
Other 2 13%
Unknown 2 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 09 January 2013.
All research outputs
#2,311,017
of 4,507,144 outputs
Outputs from Patient preference and adherence
#231
of 422 outputs
Outputs of similar age
#144,473
of 283,822 outputs
Outputs of similar age from Patient preference and adherence
#10
of 20 outputs
Altmetric has tracked 4,507,144 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 422 research outputs from this source. They receive a mean Attention Score of 2.3. This one is in the 32nd percentile – i.e., 32% 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 283,822 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20 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.