Abstract

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. 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. 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. 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. 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.

Highlights

  • Studies in social pharmacy and pharmacoepidemiology often utilize highly complex data and require the use of sophisticated methods to discern important patterns

  • We believe that Network Analysis (NA) can be a useful tool in medication use studies

  • The co-medication network is denser than the severe drug-drug interactions (DDIs) network, indicating that the drugs in the co-medication network are more connected

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Summary

Introduction

Studies in social pharmacy and pharmacoepidemiology often utilize highly complex data and require the use of sophisticated methods to discern important patterns. Data used for quantitative studies in social pharmacy and pharmacoepidemiology can be described as attribute data and relational data. Attribute data includes the characteristics of the studied objects (e.g. sex, age, medication use, sociodemographic information, etc.) while relational data contains the various relationships between subjects. The suitable way of studying attributes data is quantitative analyses, whereas, for relational data, Network Analysis (NA) is the appropriate approach 1. NA is a mathematical approach to study the relationships among nodes 3. Arrows show the direction of the relationship between nodes. The relationship does not have a specific direction. Network Analysis (NA) is a method that has been used in various disciplines such as Social sciences and Ecology for decades. We provide an introduction to NA terminology alongside a guide to creating and extracting results from the medication networks

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