Journal
BMC MEDICAL INFORMATICS AND DECISION MAKING
Volume 15, Issue -, Pages -Publisher
BMC
DOI: 10.1186/s12911-015-0140-z
Keywords
Prescription register; Modeling; Drug utilization; Pharmacoepidemiology
Categories
Funding
- Stanley Foundation
- Janssen-Cilag
- Bristol-Myers Squibb
- Eli Lilly
- Pfizer
- Lundbeck
- GlaxoSmithKline
- AstraZeneca
- Novartis
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Background: Databases of prescription drug purchases are now widely used in pharmacoepidemiologic studies. Several methods have been used to generate drug use periods from drug purchases to investigate various aspects; e.g., to study associations between exposure and outcome. Typically, such methods have been fairly simplistic, with fixed assumptions of drug use pattern and or dose (for example, the assumed usage of 1 tablet per day). This paper describes a novel PRE2DUP method that constructs drug use periods from purchase histories, and verified by a validation based on an expert evaluation of the drug use periods generated by the method. Methods: The PRE2DUP method is a novel approach based on mathematical modelling of personal drug purchasing behaviors. The method uses a decision procedure that includes each person's purchase history for each ATC code, processed in a chronological order. The method constructs exposure time periods and estimates the dose used during the period by considering the purchased amount in Defined Daily Doses (DDDs), which is recorded in the prescription register database. This method takes account of stockpiling of drugs, personal purchasing pattern; i.e., regularity of the purchases, and periods of hospital or nursing home care where drug use is not recorded in the prescription register. The method can be applied to a variety of drug classes with different doses and use patterns by controlling restriction parameters for each ATC class, or even each drug package. In the presented example, the PRE2DUP method was applied to a register-based MEDALZ-2005 study cohort. All drug purchases (3,793,085) recorded in the Finnish prescription register between 2002 and 2009 for persons with Alzheimer's disease (28,093) were included. Results: Results of the expert-opinion based validation indicate that PRE2DUP method creates drug use periods with a relatively high correctness. Drugs with varying patterns of use and drugs used on a short-term basis only require more precise parameters. Conclusions: PRE2DUP method gives highly accurate drug use periods for most drug classes, especially those meant for long-term use.
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