| The Equity in Prescription Medicines Use Study: using community pharmacy databases to study medicines utilisation. | |
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MedLine Citation:
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PMID: 20709187 Owner: NLM Status: In-Process |
Abstract/OtherAbstract:
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PURPOSE: Pharmacy dispensing databases provide a comprehensive source of data on medicines use free from many of the biases inherent in administrative databases. There are challenges associated with using pharmacy databases however. This paper describes the methods we used, and their performance, so that other researchers considering using pharmacy databases may benefit from our experiences. METHODS: Data were collected from all nine pharmacy dispensing databases in an isolated New Zealand town for the period October 2005-September 2006. Probabilistic record matching was used to link individuals across pharmacies. Patient addresses from the pharmacy data were geo-located to small areas so an area measure of socioeconomic deprivation could be assigned. Medicines were coded according to the ATC-DDD drug classification system. RESULTS: Data on 619,264 dispensings were collected. Record matching reduced an initial pool of individuals from 54,484 to 38,027. Socioeconomic deprivation ranks were assigned for 30,972 (93%) of the 33,375 unique addresses identified, or 36,048 (95%) of individuals. ATC codes were assigned to 613,490 (99%) of the dispensings, with DDDs assigned to 561,223 (91%). Overall, 93% of dispensing records had complete demographic and drug information. CONCLUSIONS: The methods described in this paper generated a rich dataset for medicines use research. These methods, while initially resource-intensive, can to a great extent be automated and applied to other locations, and will hopefully prove useful to other researchers facing similar challenges with using pharmacy databases. However, it is difficult to envisage these methods being viable on a long-term or national scale. |
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Authors:
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Simon Horsburgh; Pauline Norris; Gordon Becket; Peter Crampton; Bruce Arroll; Jacqueline Cumming; Peter Herbison; Gerald Sides |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't Date: 2010-08-13 |
Journal Detail:
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Title: Journal of biomedical informatics Volume: 43 ISSN: 1532-0480 ISO Abbreviation: J Biomed Inform Publication Date: 2010 Dec |
Date Detail:
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Created Date: 2010-11-24 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 100970413 Medline TA: J Biomed Inform Country: United States |
Other Details:
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Languages: eng Pagination: 982-7 Citation Subset: IM |
Copyright Information:
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Copyright © 2010 Elsevier Inc. All rights reserved. |
Affiliation:
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School of Pharmacy, University of Otago, Dunedin, New Zealand. simon.horsburgh@otago.ac.nz |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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