In epidemiologic studies that collect comprehensive information on medication use, the complexity of dealing with a large number of trade and generic names may limit the utilization of these data bases. This paper shows the specific advantage of using two coding systems, one to maximize efficiency of data entry, and the other to facilitate analysis by organizing the drug ingredients into hierarchical categories. The approach used by two large surveys, one in the USA and one in Italy, is described: the Established Populations for Epidemiologic Studies of the Elderly (EPESE) and the 'Gruppo Italiano di Farmacovigilanza nell' Anziano' (GIFA). To enter the medications into a computerized database, codes matching the drug product names are needed. In the EPESE the prescription and over the counter drug products are coded with the Drug Products Information Coding System (DPICS) and the Iowa Nonprescription Drug Products Information Coding System (INDPICS), respectively. The GIFA study uses the coding system of the Italian Ministry of Health (MINSAN), with a unique numeric code for each drug product available in Italy. To simplify the analytical process the drug entry codes are converted into hierarchical coding systems with unique codes for specific drug ingredients, chemical and therapeutic categories. The EPESE and GIFA drug data are coded with the Iowa Drug Information System (IDIS) ingredient codes, and the Anatomical Therapeutic and chemical (ATC) codes, respectively. Examples are provided that show coding of diuretics in these two studies and demonstrate the analytic advantages of these systems.
Pharmacology, Toxicology and Pharmaceutical Science
4
6%
Psychology
4
6%
Other
11
17%
Unknown
23
35%
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 13 June 2019.
All research outputs
#4,134,287
of 33,779,198 outputs
Outputs from European Journal of Epidemiology
#592
of 2,342 outputs
Outputs of similar age
#2,440
of 29,843 outputs
Outputs of similar age from European Journal of Epidemiology
#3
of 11 outputs
Altmetric has tracked 33,779,198 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,342 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.7. This one has gotten more attention than average, scoring higher than 74% 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 29,843 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 11 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 72% of its contemporaries.
