Presence of pharmacoepidemiology in three bibliographic databases: Medline, IPA and SCI.
OBJECTIVE
The objective of this study is to make a comparative description of the evolution and distribution of international research into pharmacoepidemiology, using three bibliographic databases, in order to select the most appropriate for future bibliometric studies.


METHODS
Bibliographic searches were performed using the following databases: Medline (1966-99), IPA (1970-99) and SCI (1990-99), using the term 'pharmacoepidemiology'. On the basis of these searches, the number of original articles per year and per journal title were noted. The growth of the output of scientific writing was found to fit Price's law.


RESULTS
A total of 845 original articles were recovered: 467 from IPA, 219 from Medline and 159 from SCI. The highest mean number of original articles per year (33.4) was obtained with the IPA database. Price's exponential growth pattern was observed among all three databases. The total numbers of journals in which the original articles were published were 102 in Medline, 65 in IPA and 60 in SCI. The journals providing a single original article comprised 65% of the Medline titles and 61% of those in IPA and SCI.


CONCLUSIONS
International research into pharmacoepidemiology presents an exponential growth pattern, in accordance with Price's law. There is a large degree of publishing dispersion. IPA was found to be the bibliographic database that recovered the greatest number of original articles, nearly half of which were published in Pharmacoepidemiology and Drug Safety. We therefore consider the latter database appropriate for bibliometric studies in the field of pharmacoepidemiology.
Arrebola-Pascual
I
I
Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy, University of Granada, Spain.
García-López
J A
JA
D015706:Bibliometrics; D016206:Databases, Bibliographic / Q000706:statistics & numerical data*; D016239:MEDLINE / Q000706:statistics & numerical data*; D017891:Pharmacoepidemiology / Q000379:methods / Q000706:statistics & numerical data*