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Identifying Off‐Label Prescriptions Through Data Mining in Danish Community Pharmacy Servers: An Exploratory Study on Desmopressin, Diclofenac, Fucidin, Mirtazapine and Quetiapine
Author(s) -
Andrulyte Monika,
Bjerrum Ole Jannik
Publication year - 2018
Publication title -
basic and clinical pharmacology and toxicology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.805
H-Index - 90
eISSN - 1742-7843
pISSN - 1742-7835
DOI - 10.1111/bcpt.13009
Subject(s) - medical prescription , pharmacy , desmopressin , quetiapine , medicine , danish , off label use , family medicine , pediatrics , emergency medicine , pharmacology , psychiatry , linguistics , philosophy , schizophrenia (object oriented programming)
The term off‐label use describes the prescription and administration of medicines outside of the terms for which it officially has been approved, including age, dose and indication. Off‐label data can be generated from the Danish National Prescription Registry through combinations with diagnoses; however, the community pharmacy servers provide equal, local, albeit less data through a faster and less constrained collection process. The data collection for this exploratory study took place at five community pharmacies in Denmark. Five drugs were chosen for the investigation and collection of prescription data across a 2‐year period. Off‐label use by age was observed to be 1.9% for diclofenac, 1.7% for desmopressin and 2.3% for quetiapine. The percentages were based on total number of 3881, 925, 2712 prescriptions, respectively. Off‐label monitored by dosage appeared to be 75% for quetiapine; by box label text analysis, off‐label indication was found to be 10–15% and 15–23% for quetiapine and mirtazapine (from a total number of 3178 prescriptions), respectively. By route of administration where fucidin ointment was applied to the nose in 60 patients, 83% were prescribed off‐label (non‐dermatological). This exploratory study revealed that pharmacy servers represent a reliable and up‐to‐date source to collect a substantial amount of raw prescription data. The method gives straightforward and simple access to analysis of off‐label use by age and dose, whereas it is possible but difficult to interpret off‐label indications and route of administration from the box label text.