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dc.contributor.authorAskar, Mohsen Gamal Saad
dc.contributor.authorNozal Cañadas, Rafael
dc.contributor.authorSvendsen, Kristian
dc.date.accessioned2022-02-09T12:30:49Z
dc.date.available2022-02-09T12:30:49Z
dc.date.issued2021-06-29
dc.description.abstractBackground - Network Analysis (NA) is a method that has been used in various disciplines such as Social sciences and Ecology for decades. So far, NA has not been used extensively in studies of medication use. Only a handful of papers have used NA in Drug Prescription Networks (DPN). We provide an introduction to NA terminology alongside a guide to creating and extracting results from the medication networks.<p> <p>Objective - To introduce the readers to NA as a tool to study medication use by demonstrating how to apply different NA measures on 3 generated medication networks.<p> <p>Methods - We used the Norwegian Prescription Database (NorPD) to create a network that describes the co-medication in elderly persons in Norway on January 1, 2013. We used the Norwegian Electronic Prescription Support System (FEST) to create another network of severe drug-drug interactions (DDIs). Lastly, we created a network combining the two networks to show the actual use of drugs with severe DDIs. We used these networks to elucidate how to apply and interpret different network measures in medication networks.<p> <p>Results - Interactive network graphs are made available online, Stata and R syntaxes are provided. Various useful network measures for medication networks were applied such as network topological features, modularity analysis and centrality measures. Edge lists data used to generate the networks are openly available for readers in an open data repository to explore and use.<p> <p>Conclusion - We believe that NA can be a useful tool in medication use studies. We have provided information and hopefully inspiration for other researchers to use NA in their own projects. While network analyses are useful for exploring and discovering structures in medication use studies, it also has limitations. It can be challenging to interpret and it is not suitable for hypothesis testing.en_US
dc.identifier.citationAskar MGS, Nozal Cañadas, Svendsen. An introduction to network analysis for studies of medication use. Research in Social and Administrative Pharmacy. 2021en_US
dc.identifier.cristinIDFRIDAID 1983366
dc.identifier.doi10.1016/j.sapharm.2021.06.021
dc.identifier.issn1551-7411
dc.identifier.issn1934-8150
dc.identifier.urihttps://hdl.handle.net/10037/23995
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.ispartofNozal Cañadas, R.A. (2024). Epidemiology Network Analysis. (Doctoral thesis). <a href=https://hdl.handle.net/10037/35572>https://hdl.handle.net/10037/35572</a>
dc.relation.journalResearch in Social and Administrative Pharmacy
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2021 The Author(s)en_US
dc.titleAn introduction to network analysis for studies of medication useen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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