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...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Gianluca Miglio [verfasserIn] Lara Basso [verfasserIn] Lucrezia G. Armando [verfasserIn] Sara Traina [verfasserIn] Elisa Benetti [verfasserIn] Abdoulaye Diarassouba [verfasserIn] Raffaella Baroetto Parisi [verfasserIn] Mariangela Esiliato [verfasserIn] Cristina Rolando [verfasserIn] Elisa Remani [verfasserIn] Clara Cena [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	drug prescriptions networks pattern recognition

Übergeordnetes Werk:	In: International Journal of Environmental Research and Public Health - MDPI AG, 2005, 18(2021), 4859, p 4859
Übergeordnetes Werk:	volume:18 ; year:2021 ; number:4859, p 4859

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.3390/ijerph18094859

Katalog-ID:	DOAJ067360343

Internformat


LEADER	01000caa a22002652 4500
001	DOAJ067360343
003	DE-627
005	20230309070334.0
007	cr uuu---uuuuu
008	230228s2021 xx \|\|\|\|\|o 00\| \|\|eng c
024	7		\|a 10.3390/ijerph18094859 \|2 doi
035			\|a (DE-627)DOAJ067360343
035			\|a (DE-599)DOAJb88af5f81e9949a2b5d5ae913db82650
040			\|a DE-627 \|b ger \|c DE-627 \|e rakwb
041			\|a eng
100	0		\|a Gianluca Miglio \|e verfasserin \|4 aut
245	1	2	\|a A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy)
264		1	\|c 2021
336			\|a Text \|b txt \|2 rdacontent
337			\|a Computermedien \|b c \|2 rdamedia
338			\|a Online-Ressource \|b cr \|2 rdacarrier
520			\|a 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.
650		4	\|a drug prescriptions
650		4	\|a networks
650		4	\|a pattern recognition
653		0	\|a Medicine
653		0	\|a R
700	0		\|a Lara Basso \|e verfasserin \|4 aut
700	0		\|a Lucrezia G. Armando \|e verfasserin \|4 aut
700	0		\|a Sara Traina \|e verfasserin \|4 aut
700	0		\|a Elisa Benetti \|e verfasserin \|4 aut
700	0		\|a Abdoulaye Diarassouba \|e verfasserin \|4 aut
700	0		\|a Raffaella Baroetto Parisi \|e verfasserin \|4 aut
700	0		\|a Mariangela Esiliato \|e verfasserin \|4 aut
700	0		\|a Cristina Rolando \|e verfasserin \|4 aut
700	0		\|a Elisa Remani \|e verfasserin \|4 aut
700	0		\|a Clara Cena \|e verfasserin \|4 aut
773	0	8	\|i In \|t International Journal of Environmental Research and Public Health \|d MDPI AG, 2005 \|g 18(2021), 4859, p 4859 \|w (DE-627)477992463 \|w (DE-600)2175195-X \|x 16604601 \|7 nnns
773	1	8	\|g volume:18 \|g year:2021 \|g number:4859, p 4859
856	4	0	\|u https://doi.org/10.3390/ijerph18094859 \|z kostenfrei
856	4	0	\|u https://doaj.org/article/b88af5f81e9949a2b5d5ae913db82650 \|z kostenfrei
856	4	0	\|u https://www.mdpi.com/1660-4601/18/9/4859 \|z kostenfrei
856	4	2	\|u https://doaj.org/toc/1661-7827 \|y Journal toc \|z kostenfrei
856	4	2	\|u https://doaj.org/toc/1660-4601 \|y Journal toc \|z kostenfrei
912			\|a GBV_USEFLAG_A
912			\|a SYSFLAG_A
912			\|a GBV_DOAJ
912			\|a GBV_ILN_20
912			\|a GBV_ILN_22
912			\|a GBV_ILN_23
912			\|a GBV_ILN_24
912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_95
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_151
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_206
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2153
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4367
912			\|a GBV_ILN_4700
951			\|a AR
952			\|d 18 \|j 2021 \|e 4859, p 4859

Indexfelder

author_variant	g m gm l b lb l g a lga s t st e b eb a d ad r b p rbp m e me c r cr e r er c c cc
matchkey_str	article:16604601:2021----::ntokprahotetdodupecitosnlssfdiitaieeodfoaoaha
hierarchy_sort_str	2021
publishDate	2021
allfields	10.3390/ijerph18094859 doi (DE-627)DOAJ067360343 (DE-599)DOAJb88af5f81e9949a2b5d5ae913db82650 DE-627 ger DE-627 rakwb eng Gianluca Miglio verfasserin aut A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy) 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. drug prescriptions networks pattern recognition Medicine R Lara Basso verfasserin aut Lucrezia G. Armando verfasserin aut Sara Traina verfasserin aut Elisa Benetti verfasserin aut Abdoulaye Diarassouba verfasserin aut Raffaella Baroetto Parisi verfasserin aut Mariangela Esiliato verfasserin aut Cristina Rolando verfasserin aut Elisa Remani verfasserin aut Clara Cena verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 18(2021), 4859, p 4859 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:18 year:2021 number:4859, p 4859 https://doi.org/10.3390/ijerph18094859 kostenfrei https://doaj.org/article/b88af5f81e9949a2b5d5ae913db82650 kostenfrei https://www.mdpi.com/1660-4601/18/9/4859 kostenfrei https://doaj.org/toc/1661-7827 Journal toc kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 4859, p 4859
spelling	10.3390/ijerph18094859 doi (DE-627)DOAJ067360343 (DE-599)DOAJb88af5f81e9949a2b5d5ae913db82650 DE-627 ger DE-627 rakwb eng Gianluca Miglio verfasserin aut A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy) 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. drug prescriptions networks pattern recognition Medicine R Lara Basso verfasserin aut Lucrezia G. Armando verfasserin aut Sara Traina verfasserin aut Elisa Benetti verfasserin aut Abdoulaye Diarassouba verfasserin aut Raffaella Baroetto Parisi verfasserin aut Mariangela Esiliato verfasserin aut Cristina Rolando verfasserin aut Elisa Remani verfasserin aut Clara Cena verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 18(2021), 4859, p 4859 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:18 year:2021 number:4859, p 4859 https://doi.org/10.3390/ijerph18094859 kostenfrei https://doaj.org/article/b88af5f81e9949a2b5d5ae913db82650 kostenfrei https://www.mdpi.com/1660-4601/18/9/4859 kostenfrei https://doaj.org/toc/1661-7827 Journal toc kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 4859, p 4859
allfields_unstemmed	10.3390/ijerph18094859 doi (DE-627)DOAJ067360343 (DE-599)DOAJb88af5f81e9949a2b5d5ae913db82650 DE-627 ger DE-627 rakwb eng Gianluca Miglio verfasserin aut A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy) 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. drug prescriptions networks pattern recognition Medicine R Lara Basso verfasserin aut Lucrezia G. Armando verfasserin aut Sara Traina verfasserin aut Elisa Benetti verfasserin aut Abdoulaye Diarassouba verfasserin aut Raffaella Baroetto Parisi verfasserin aut Mariangela Esiliato verfasserin aut Cristina Rolando verfasserin aut Elisa Remani verfasserin aut Clara Cena verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 18(2021), 4859, p 4859 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:18 year:2021 number:4859, p 4859 https://doi.org/10.3390/ijerph18094859 kostenfrei https://doaj.org/article/b88af5f81e9949a2b5d5ae913db82650 kostenfrei https://www.mdpi.com/1660-4601/18/9/4859 kostenfrei https://doaj.org/toc/1661-7827 Journal toc kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 4859, p 4859
allfieldsGer	10.3390/ijerph18094859 doi (DE-627)DOAJ067360343 (DE-599)DOAJb88af5f81e9949a2b5d5ae913db82650 DE-627 ger DE-627 rakwb eng Gianluca Miglio verfasserin aut A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy) 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. drug prescriptions networks pattern recognition Medicine R Lara Basso verfasserin aut Lucrezia G. Armando verfasserin aut Sara Traina verfasserin aut Elisa Benetti verfasserin aut Abdoulaye Diarassouba verfasserin aut Raffaella Baroetto Parisi verfasserin aut Mariangela Esiliato verfasserin aut Cristina Rolando verfasserin aut Elisa Remani verfasserin aut Clara Cena verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 18(2021), 4859, p 4859 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:18 year:2021 number:4859, p 4859 https://doi.org/10.3390/ijerph18094859 kostenfrei https://doaj.org/article/b88af5f81e9949a2b5d5ae913db82650 kostenfrei https://www.mdpi.com/1660-4601/18/9/4859 kostenfrei https://doaj.org/toc/1661-7827 Journal toc kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 4859, p 4859
allfieldsSound	10.3390/ijerph18094859 doi (DE-627)DOAJ067360343 (DE-599)DOAJb88af5f81e9949a2b5d5ae913db82650 DE-627 ger DE-627 rakwb eng Gianluca Miglio verfasserin aut A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy) 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. drug prescriptions networks pattern recognition Medicine R Lara Basso verfasserin aut Lucrezia G. Armando verfasserin aut Sara Traina verfasserin aut Elisa Benetti verfasserin aut Abdoulaye Diarassouba verfasserin aut Raffaella Baroetto Parisi verfasserin aut Mariangela Esiliato verfasserin aut Cristina Rolando verfasserin aut Elisa Remani verfasserin aut Clara Cena verfasserin aut In International Journal of Environmental Research and Public Health MDPI AG, 2005 18(2021), 4859, p 4859 (DE-627)477992463 (DE-600)2175195-X 16604601 nnns volume:18 year:2021 number:4859, p 4859 https://doi.org/10.3390/ijerph18094859 kostenfrei https://doaj.org/article/b88af5f81e9949a2b5d5ae913db82650 kostenfrei https://www.mdpi.com/1660-4601/18/9/4859 kostenfrei https://doaj.org/toc/1661-7827 Journal toc kostenfrei https://doaj.org/toc/1660-4601 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2021 4859, p 4859
language	English
source	In International Journal of Environmental Research and Public Health 18(2021), 4859, p 4859 volume:18 year:2021 number:4859, p 4859
sourceStr	In International Journal of Environmental Research and Public Health 18(2021), 4859, p 4859 volume:18 year:2021 number:4859, p 4859
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	drug prescriptions networks pattern recognition Medicine R
isfreeaccess_bool	true
container_title	International Journal of Environmental Research and Public Health
authorswithroles_txt_mv	Gianluca Miglio @@aut@@ Lara Basso @@aut@@ Lucrezia G. Armando @@aut@@ Sara Traina @@aut@@ Elisa Benetti @@aut@@ Abdoulaye Diarassouba @@aut@@ Raffaella Baroetto Parisi @@aut@@ Mariangela Esiliato @@aut@@ Cristina Rolando @@aut@@ Elisa Remani @@aut@@ Clara Cena @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	477992463
id	DOAJ067360343
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ067360343</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230309070334.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230228s2021 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3390/ijerph18094859</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ067360343</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJb88af5f81e9949a2b5d5ae913db82650</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Gianluca Miglio</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="2"><subfield code="a">A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy)</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">drug prescriptions</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">networks</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">pattern recognition</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Medicine</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">R</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Lara Basso</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Lucrezia G. Armando</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Sara Traina</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Elisa Benetti</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Abdoulaye Diarassouba</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Raffaella Baroetto Parisi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Mariangela Esiliato</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Cristina Rolando</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Elisa Remani</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Clara Cena</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">International Journal of Environmental Research and Public Health</subfield><subfield code="d">MDPI AG, 2005</subfield><subfield code="g">18(2021), 4859, p 4859</subfield><subfield code="w">(DE-627)477992463</subfield><subfield code="w">(DE-600)2175195-X</subfield><subfield code="x">16604601</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:18</subfield><subfield code="g">year:2021</subfield><subfield code="g">number:4859, p 4859</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3390/ijerph18094859</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/b88af5f81e9949a2b5d5ae913db82650</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.mdpi.com/1660-4601/18/9/4859</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1661-7827</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1660-4601</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">18</subfield><subfield code="j">2021</subfield><subfield code="e">4859, p 4859</subfield></datafield></record></collection>
author	Gianluca Miglio
spellingShingle	Gianluca Miglio misc drug prescriptions misc networks misc pattern recognition misc Medicine misc R A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy)
authorStr	Gianluca Miglio
ppnlink_with_tag_str_mv	@@773@@(DE-627)477992463
format	electronic Article
delete_txt_mv	keep
author_role	aut aut aut aut aut aut aut aut aut aut aut
collection	DOAJ
remote_str	true
illustrated	Not Illustrated
issn	16604601
topic_title	A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy) drug prescriptions networks pattern recognition
topic	misc drug prescriptions misc networks misc pattern recognition misc Medicine misc R
topic_unstemmed	misc drug prescriptions misc networks misc pattern recognition misc Medicine misc R
topic_browse	misc drug prescriptions misc networks misc pattern recognition misc Medicine misc R
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
format_main_str_mv	Text Zeitschrift/Artikel
carriertype_str_mv	cr
hierarchy_parent_title	International Journal of Environmental Research and Public Health
hierarchy_parent_id	477992463
hierarchy_top_title	International Journal of Environmental Research and Public Health
isfreeaccess_txt	true
familylinks_str_mv	(DE-627)477992463 (DE-600)2175195-X
title	A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy)
ctrlnum	(DE-627)DOAJ067360343 (DE-599)DOAJb88af5f81e9949a2b5d5ae913db82650
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)
author_sort	Gianluca Miglio
journal	International Journal of Environmental Research and Public Health
journalStr	International Journal of Environmental Research and Public Health
lang_code	eng
isOA_bool	true
recordtype	marc
publishDateSort	2021
contenttype_str_mv	txt
author_browse	Gianluca Miglio Lara Basso Lucrezia G. Armando Sara Traina Elisa Benetti Abdoulaye Diarassouba Raffaella Baroetto Parisi Mariangela Esiliato Cristina Rolando Elisa Remani Clara Cena
container_volume	18
format_se	Elektronische Aufsätze
author-letter	Gianluca Miglio
doi_str_mv	10.3390/ijerph18094859
author2-role	verfasserin
title_sort	network approach for the study of drug prescriptions: analysis of administrative records from a local health unit (asl to4, regione piemonte, italy)
title_auth	A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy)
abstract	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.
abstractGer	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.
abstract_unstemmed	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.
collection_details	GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2153 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700
container_issue	4859, p 4859
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)
url	https://doi.org/10.3390/ijerph18094859 https://doaj.org/article/b88af5f81e9949a2b5d5ae913db82650 https://www.mdpi.com/1660-4601/18/9/4859 https://doaj.org/toc/1661-7827 https://doaj.org/toc/1660-4601
remote_bool	true
author2	Lara Basso Lucrezia G. Armando Sara Traina Elisa Benetti Abdoulaye Diarassouba Raffaella Baroetto Parisi Mariangela Esiliato Cristina Rolando Elisa Remani Clara Cena
author2Str	Lara Basso Lucrezia G. Armando Sara Traina Elisa Benetti Abdoulaye Diarassouba Raffaella Baroetto Parisi Mariangela Esiliato Cristina Rolando Elisa Remani Clara Cena
ppnlink	477992463
mediatype_str_mv	c
isOA_txt	true
hochschulschrift_bool	false
doi_str	10.3390/ijerph18094859
up_date	2024-07-04T00:35:35.822Z
_version_	1803606646664986624
fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ067360343</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230309070334.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230228s2021 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.3390/ijerph18094859</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ067360343</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJb88af5f81e9949a2b5d5ae913db82650</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Gianluca Miglio</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="2"><subfield code="a">A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy)</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">drug prescriptions</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">networks</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">pattern recognition</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Medicine</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">R</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Lara Basso</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Lucrezia G. Armando</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Sara Traina</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Elisa Benetti</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Abdoulaye Diarassouba</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Raffaella Baroetto Parisi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Mariangela Esiliato</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Cristina Rolando</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Elisa Remani</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Clara Cena</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">International Journal of Environmental Research and Public Health</subfield><subfield code="d">MDPI AG, 2005</subfield><subfield code="g">18(2021), 4859, p 4859</subfield><subfield code="w">(DE-627)477992463</subfield><subfield code="w">(DE-600)2175195-X</subfield><subfield code="x">16604601</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:18</subfield><subfield code="g">year:2021</subfield><subfield code="g">number:4859, p 4859</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.3390/ijerph18094859</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/b88af5f81e9949a2b5d5ae913db82650</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.mdpi.com/1660-4601/18/9/4859</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1661-7827</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1660-4601</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_206</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_224</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2153</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">18</subfield><subfield code="j">2021</subfield><subfield code="e">4859, p 4859</subfield></datafield></record></collection>
score	7.3987913

Nicht das Richtige dabei?

Schreiben Sie uns!

A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy)

Nicht das Richtige dabei?

Zugang & Verfügbarkeit

Vorhandene Bände

Nicht das Richtige dabei?