Suppr超能文献

2019年至2023年美国药房和医院中丁丙诺啡分布模式分析。

Analysis of buprenorphine distribution patterns among pharmacies and hospitals in the USA from 2019 to 2023.

作者信息

Gikoska Maria, Florio Anna K, George Andrew, Piper Brian J

机构信息

Geisinger Commonwealth School of Medicine, Scranton, Pennsylvania, USA

Geisinger Commonwealth School of Medicine, Scranton, Pennsylvania, USA.

出版信息

BMJ Open. 2025 Jul 20;15(7):e094454. doi: 10.1136/bmjopen-2024-094454.

Abstract

BACKGROUND

Opioid use disorder (OUD) is a debilitating condition characterised by the overuse of opioid medications and the development of physical and/or psychological dependence. Consequences of this condition include chronic impairment, distress and later life-altering health conditions such as overdose, all of which have been highlighted by the prominence of OUD in the USA in recent years. Buprenorphine is a standard OUD treatment and commonly used for pain management. Understanding changes in distribution patterns across the USA is vital for continuing to improve outcomes for OUD patients.

METHODS

This study used the Drug Enforcement Administration's Automated Reports and Consolidated Ordering System (ARCOS) and the US Census Bureau Population Estimates databases to analyse changes in buprenorphine distribution among pharmacies and hospitals from 2019 to 2023, to determine temporal patterns and to identify state-level disparities using the data. The data were corrected for population to identify patterns of buprenorphine distribution in the USA from 2021 to 2022 and 2022 to 2023 through examining percent changes in milligrams per 100 population at the national and state levels.

RESULTS

The year-to-year percent change of national buprenorphine distribution from pharmacies has remained positive but changed from a 12.2% increase from 2019 to 2020 (figure 4) to a four per cent increase every year from 2020 to 2023. From 2021 to 2022, there was a +4.9% increase in total grams of buprenorphine distributed to pharmacies and a 95% CI [-5.1, 14.9], with the District of Columbia, South Dakota and Nebraska outside of the 95% CI. Distribution to hospitals increased by 10.2% [-32.3, 52.7] during 2021-2022, with Hawaii, New Hampshire and Delaware being outside of 95% CI. From 2022 to 2023, there was an increase of +5.7% and 95% CI [-3.5, 14.9] in pharmacy distribution, with states including Washington, Rhode Island and Kansas remain outside of the 95% CI. Hospital distribution has decreased from twenty per cent between 2019 and 2020 (figure 4) to eighteen per cent between 2022 and 2023.

CONCLUSION

Following increases in buprenorphine distribution during the COVID pandemic, a consistent increase has continued year-over-year in most states and the country overall by both pharmacies and hospitals. Some states (eg, Rhode Island, Georgia, District of Columbia) have not followed this pattern. Notably, Hawaii went from the most negative percent change in hospital distribution to the most positive change in the timeframe analysed. This may offer opportunities to analyse more specific impacts of the increased buprenorphine distribution on populations and their outcomes associated with OUD.

摘要

背景

阿片类药物使用障碍(OUD)是一种使人衰弱的疾病,其特征是阿片类药物的过度使用以及身体和/或心理依赖的形成。这种疾病的后果包括慢性损伤、痛苦以及后期改变生活的健康状况,如药物过量,近年来美国OUD的突出情况凸显了所有这些后果。丁丙诺啡是一种标准的OUD治疗药物,常用于疼痛管理。了解美国各地分布模式的变化对于持续改善OUD患者的治疗效果至关重要。

方法

本研究使用美国缉毒局的自动报告和综合订购系统(ARCOS)以及美国人口普查局的人口估计数据库,分析2019年至2023年期间药店和医院中丁丙诺啡分布的变化,以确定时间模式并使用这些数据识别州级差异。通过检查国家和州层面每100人口中毫克数的百分比变化,对数据进行人口校正,以确定2021年至2022年以及2022年至2023年美国丁丙诺啡的分布模式。

结果

药店丁丙诺啡全国分布的逐年百分比变化一直呈正值,但从2019年至2020年的12.2%增长(图4)变为2020年至2023年每年4%的增长。从2021年到2022年,分配给药店的丁丙诺啡总克数增加了4.9%,95%置信区间为[-5.1, 14.9],哥伦比亚特区、南达科他州和内布拉斯加州不在95%置信区间内。2021 - 2022年期间,医院的分配量增加了10.2%[-32.3, 52.7],夏威夷、新罕布什尔州和特拉华州不在95%置信区间内。从2022年到2023年,药店分配量增加了5.7%,95%置信区间为[-3.5, 14.9],包括华盛顿州、罗德岛州和堪萨斯州等州不在95%置信区间内。医院分配量已从2019年至2020年期间的20%下降到2022年至2023年期间的18%。

结论

在新冠疫情期间丁丙诺啡分布增加之后,大多数州以及整个国家的药店和医院的丁丙诺啡分布量持续逐年增加。一些州(如罗德岛州、佐治亚州、哥伦比亚特区)并未遵循这一模式。值得注意的是,在分析的时间范围内,夏威夷从医院分配量百分比变化最负变为最正。这可能为分析丁丙诺啡分布增加对人群及其与OUD相关的结果的更具体影响提供机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07d1/12278134/f64f268ffa74/bmjopen-15-7-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验