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A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy)
In a Drug Prescription Network (DPN), each drug is represented as a node and two drugs co-prescribed to the same patient are represented as an edge linking the nodes. The use of DPNs is a novel approach that has been proposed as a means to study the complexity of drug prescription. The aim of this s...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8125782/ https://www.ncbi.nlm.nih.gov/pubmed/34063257 http://dx.doi.org/10.3390/ijerph18094859 |
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author | Miglio, Gianluca Basso, Lara Armando, Lucrezia G. Traina, Sara Benetti, Elisa Diarassouba, Abdoulaye Baroetto Parisi, Raffaella Esiliato, Mariangela Rolando, Cristina Remani, Elisa Cena, Clara |
author_facet | Miglio, Gianluca Basso, Lara Armando, Lucrezia G. Traina, Sara Benetti, Elisa Diarassouba, Abdoulaye Baroetto Parisi, Raffaella Esiliato, Mariangela Rolando, Cristina Remani, Elisa Cena, Clara |
author_sort | Miglio, Gianluca |
collection | PubMed |
description | In a Drug Prescription Network (DPN), each drug is represented as a node and two drugs co-prescribed to the same patient are represented as an edge linking the nodes. The use of DPNs is a novel approach that has been proposed as a means to study the complexity of drug prescription. The aim of this study is to demonstrate the analytical power of the DPN-based approach when it is applied to the analysis of administrative data. Drug prescription data that were collected at a local health unit (ASL TO4, Regione Piemonte, Italy), over a 12-month period (July 2018–June 2019), were used to create several DPNs that correspond to the five levels of the Anatomical Therapeutic Chemical classification system. A total of 5,431,335 drugs prescribed to 361,574 patients (age 0–100 years; 54.7% females) were analysed. As indicated by our results, the DPNs were dense networks, with giant components that contain all nodes. The disassortative mixing of node degrees was observed, which implies that non-random connectivity exists in the networks. Network-based methods have proven to be a flexible and efficient approach to the analysis of administrative data on drug prescription. |
format | Online Article Text |
id | pubmed-8125782 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-81257822021-05-17 A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy) Miglio, Gianluca Basso, Lara Armando, Lucrezia G. Traina, Sara Benetti, Elisa Diarassouba, Abdoulaye Baroetto Parisi, Raffaella Esiliato, Mariangela Rolando, Cristina Remani, Elisa Cena, Clara Int J Environ Res Public Health Article In a Drug Prescription Network (DPN), each drug is represented as a node and two drugs co-prescribed to the same patient are represented as an edge linking the nodes. The use of DPNs is a novel approach that has been proposed as a means to study the complexity of drug prescription. The aim of this study is to demonstrate the analytical power of the DPN-based approach when it is applied to the analysis of administrative data. Drug prescription data that were collected at a local health unit (ASL TO4, Regione Piemonte, Italy), over a 12-month period (July 2018–June 2019), were used to create several DPNs that correspond to the five levels of the Anatomical Therapeutic Chemical classification system. A total of 5,431,335 drugs prescribed to 361,574 patients (age 0–100 years; 54.7% females) were analysed. As indicated by our results, the DPNs were dense networks, with giant components that contain all nodes. The disassortative mixing of node degrees was observed, which implies that non-random connectivity exists in the networks. Network-based methods have proven to be a flexible and efficient approach to the analysis of administrative data on drug prescription. MDPI 2021-05-02 /pmc/articles/PMC8125782/ /pubmed/34063257 http://dx.doi.org/10.3390/ijerph18094859 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Miglio, Gianluca Basso, Lara Armando, Lucrezia G. Traina, Sara Benetti, Elisa Diarassouba, Abdoulaye Baroetto Parisi, Raffaella Esiliato, Mariangela Rolando, Cristina Remani, Elisa Cena, Clara A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy) |
title | A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy) |
title_full | A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy) |
title_fullStr | A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy) |
title_full_unstemmed | A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy) |
title_short | A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy) |
title_sort | network approach for the study of drug prescriptions: analysis of administrative records from a local health unit (asl to4, regione piemonte, italy) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8125782/ https://www.ncbi.nlm.nih.gov/pubmed/34063257 http://dx.doi.org/10.3390/ijerph18094859 |
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