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Drug utilization, prescription errors and potential drug-drug interactions: an experience in rural Sri Lanka

Overview of attention for article published in BMC Pharmacology and Toxicology, June 2016
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  • Good Attention Score compared to outputs of the same age (69th percentile)

Mentioned by

policy
1 policy source
twitter
1 tweeter

Citations

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18 Dimensions

Readers on

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65 Mendeley
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Title
Drug utilization, prescription errors and potential drug-drug interactions: an experience in rural Sri Lanka
Published in
BMC Pharmacology and Toxicology, June 2016
DOI 10.1186/s40360-016-0071-z
Pubmed ID
Authors

Devarajan Rathish, Sivaswamy Bahini, Thanikai Sivakumar, Thilani Thiranagama, Tharmarajah Abarajithan, Buddhika Wijerathne, Channa Jayasumana, Sisira Siribaddana

Abstract

Prescription writing is a process which transfers the therapeutic message from the prescriber to the patient through the pharmacist. Prescribing errors, drug duplication and potential drug-drug interactions (pDDI) in prescriptions lead to medication error. Assessment of the above was made in prescriptions dispensed at State Pharmaceutical Corporation (SPC), Anuradhapura, Sri Lanka. A cross sectional study was conducted. Drugs were classified according to the WHO anatomical, therapeutic chemical classification system. A three point Likert scale, a checklist and Medscape online drug interaction checker were used to assess legibility, completeness and pDDIs respectively. Thousand prescriptions were collected. Majority were hand written (99.8 %) and from the private sector (73 %). The most frequently prescribed substance and subgroup were atorvastatin (4 %, n = 3668) and proton pump inhibitors (7 %, n = 3668) respectively. Out of the substances prescribed from the government and private sectors, 59 and 50 % respectively were available in the national list of essential medicines, Sri Lanka. Patients address (5 %), Sri Lanka Medical Council (SLMC) registration number (35 %), route (7 %), generic name (16 %), treatment symbol (48 %), diagnosis (41 %) and refill information (6 %) were seen in less than half of the prescriptions. Most were legible with effort (65 %) and illegibility was seen in 9 %. There was significant difference in omission and/or errors of generic name (P = 0.000), dose (P = 0.000), SLMC registration number (P = 0.000), and in evidence of pDDI (P = 0.009) with regards to the sector of prescribing. The commonest subgroup involved in duplication was non-steroidal anti-inflammatory drugs (NSAIDs) (43 %; 56/130). There were 1376 potential drug interactions (466/887 prescriptions). Most common pair causing pDDI was aspirin with losartan (4 %, n = 1376). Atorvastatin was the most frequently prescribed substance. Fifteen percent of the prescriptions originate from government sector. SLMC registration number and trade names were seen more in prescriptions originating from the private sector. Most prescriptions were legible with effort. NSAIDs were the commonest implicated in drug class duplication. Fifty three percent of prescriptions have pDDI.

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 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 3%
Sri Lanka 2 3%
Unknown 61 94%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 16 25%
Student > Master 8 12%
Student > Doctoral Student 7 11%
Researcher 5 8%
Other 5 8%
Other 12 18%
Unknown 12 18%
Readers by discipline Count As %
Medicine and Dentistry 21 32%
Pharmacology, Toxicology and Pharmaceutical Science 17 26%
Nursing and Health Professions 6 9%
Biochemistry, Genetics and Molecular Biology 2 3%
Agricultural and Biological Sciences 2 3%
Other 6 9%
Unknown 11 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 01 January 2019.
All research outputs
#4,866,748
of 17,361,274 outputs
Outputs from BMC Pharmacology and Toxicology
#91
of 350 outputs
Outputs of similar age
#79,223
of 267,789 outputs
Outputs of similar age from BMC Pharmacology and Toxicology
#2
of 3 outputs
Altmetric has tracked 17,361,274 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 350 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has gotten more attention than average, scoring higher than 73% 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 267,789 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 69% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.