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

• Published in: Scientific reports Vol. 11; no. 1; p. 7142
• Main Authors: Nagarajan, Radhakrishnan, Talbert, Jeffery, Miller, Craig S., Ebersole, Jeffrey
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 30.03.2021; Nature Publishing Group; Nature Portfolio
• Subjects: 639/705/1046; 692/700; 692/700/1538; 692/700/3032; Acetaminophen; Analgesics; Community structure; Drug abuse; Humanities and Social Sciences; Medicaid; multidisciplinary; Opioids; Science; Science (multidisciplinary)
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-86409-6

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.