Surveillance of Physicians Causing Potential Drug-Drug Interactions in Ambulatory Care: A Pilot Study in Switzerland
Author(s) -
Heiner C. Bucher,
Rita Achermann,
Nadja A. Stohler,
Christoph Meier
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0147606
Subject(s) - formulary , ambulatory , medicine , medical prescription , ambulatory care , specialty , drug , emergency medicine , health care , family medicine , pharmacology , economics , economic growth
Objectives We analysed potential drug-drug interactions (DDI) in ambulatory care in Switzerland based on claims data from three large health insurers in 2010 to identify physicians with peculiar prescription behaviour differing from peers of the same specialty. Methods We analysed contraindicated or potentially contraindicated DDI from the national drug formulary and calculated for each physician the ratios of the number of patients with a potential DDI divided by the number of patients at risk and used a zero inflated binomial distribution to correct for the inflated number of observations with no DDI. We then calculated the probability that the number of caused potential DDI of physicians was unlikely (p-value < 0.05 and ≥0.01) and very unlikely (p-value <0.01) to be due to chance. Results Of 1'607'233 females and 1'525'307 males 1.3% and 1.2% were exposed to at least one potential DDI during 12 months. When analysing the 40 most common DDI, 598 and 416 of 18,297 physicians (3.3% and 2.3%) were causing potential DDI in a frequency unlikely (p<0.05 and p≥0.01) and very unlikely (p<0.01) to be explained by chance. Patients cared by general practitioners and cardiologists had the lowest probability (0.20 and 0.26) for not being exposed to DDI. Conclusions Contraindicated or potentially contraindicated DDI are frequent in ambulatory care in Switzerland, with a small proportion of physicians causing potential DDI in a frequency that is very unlikely to be explained by chance when compared to peers of the same specialty.
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