Variations in Schedule III prescription patterns in a Medicaid population pre- and post-policy

Abstract The present study investigated variations in patient movement patterns between prescribers before and after House Bill 1 (HB1) implementation in Kentucky using network abstractions (PPN: prescriber-prescriber networks) from a one-month cross-sectional Schedule III prescription data in a Med...

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Autores principales:	Radhakrishnan Nagarajan, Jeffery Talbert, Craig S. Miller, Jeffrey Ebersole
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d08f68dd02474bbd96ed3ac15e9da2ed
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spelling	oai:doaj.org-article:d08f68dd02474bbd96ed3ac15e9da2ed2021-12-02T13:26:50ZVariations in Schedule III prescription patterns in a Medicaid population pre- and post-policy10.1038/s41598-021-86409-62045-2322https://doaj.org/article/d08f68dd02474bbd96ed3ac15e9da2ed2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86409-6https://doaj.org/toc/2045-2322Abstract The present study investigated variations in patient movement patterns between prescribers before and after House Bill 1 (HB1) implementation in Kentucky using network abstractions (PPN: prescriber-prescriber networks) from a one-month cross-sectional Schedule III prescription data in a Medicaid population. Network characteristics such as degree centrality distribution of PPN was positively skewed and revealed Dental Practitioners to be the highly connected specialty with opioid analgesic hydrocodone-acetaminophen to be the most commonly prescribed drug. Taxonomy enrichment of the prescriber specialties in PPN using chi-square test revealed a reduction in the enriched taxonomies Post-HB1 compared to Pre-HB1 with Dental practitioners being constitutively enriched (p < 0.05). PPNs were also found to exhibit rich community structure revealing inherent clustering of prescribers as a result of patient movement, and were markedly different from those generated by random graph models. The magnitude of deviation from random graphs decreased Post-HB1 relative to Pre-HB1. The proposed network approach provides system-level insights into prescribers with potential to complement classical reductionist approaches and aggregate statistical measures used in assessing changes in prescription patterns pre- and post- policy implementation. It can provide preliminary cues into drug seeking behavior, and facilitate targeted surveillance of prescriber communities.Radhakrishnan NagarajanJeffery TalbertCraig S. MillerJeffrey EbersoleNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Radhakrishnan Nagarajan Jeffery Talbert Craig S. Miller Jeffrey Ebersole Variations in Schedule III prescription patterns in a Medicaid population pre- and post-policy
description	Abstract The present study investigated variations in patient movement patterns between prescribers before and after House Bill 1 (HB1) implementation in Kentucky using network abstractions (PPN: prescriber-prescriber networks) from a one-month cross-sectional Schedule III prescription data in a Medicaid population. Network characteristics such as degree centrality distribution of PPN was positively skewed and revealed Dental Practitioners to be the highly connected specialty with opioid analgesic hydrocodone-acetaminophen to be the most commonly prescribed drug. Taxonomy enrichment of the prescriber specialties in PPN using chi-square test revealed a reduction in the enriched taxonomies Post-HB1 compared to Pre-HB1 with Dental practitioners being constitutively enriched (p < 0.05). PPNs were also found to exhibit rich community structure revealing inherent clustering of prescribers as a result of patient movement, and were markedly different from those generated by random graph models. The magnitude of deviation from random graphs decreased Post-HB1 relative to Pre-HB1. The proposed network approach provides system-level insights into prescribers with potential to complement classical reductionist approaches and aggregate statistical measures used in assessing changes in prescription patterns pre- and post- policy implementation. It can provide preliminary cues into drug seeking behavior, and facilitate targeted surveillance of prescriber communities.
format	article
author	Radhakrishnan Nagarajan Jeffery Talbert Craig S. Miller Jeffrey Ebersole
author_facet	Radhakrishnan Nagarajan Jeffery Talbert Craig S. Miller Jeffrey Ebersole
author_sort	Radhakrishnan Nagarajan
title	Variations in Schedule III prescription patterns in a Medicaid population pre- and post-policy
title_short	Variations in Schedule III prescription patterns in a Medicaid population pre- and post-policy
title_full	Variations in Schedule III prescription patterns in a Medicaid population pre- and post-policy
title_fullStr	Variations in Schedule III prescription patterns in a Medicaid population pre- and post-policy
title_full_unstemmed	Variations in Schedule III prescription patterns in a Medicaid population pre- and post-policy
title_sort	variations in schedule iii prescription patterns in a medicaid population pre- and post-policy
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/d08f68dd02474bbd96ed3ac15e9da2ed
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Variations in Schedule III prescription patterns in a Medicaid population pre- and post-policy

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