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处方药物监测项目的分类:对 1999 年至 2016 年项目演变的潜在转移分析。

A typology of prescription drug monitoring programs: a latent transition analysis of the evolution of programs from 1999 to 2016.

机构信息

Violence Prevention Research Program, Department of Emergency Medicine, UC Davis School of Medicine, CA, USA.

Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.

出版信息

Addiction. 2019 Feb;114(2):248-258. doi: 10.1111/add.14440. Epub 2018 Oct 22.

Abstract

BACKGROUND AND AIMS

Prescription drug monitoring programs (PDMP), defined as state-level databases used in the United States that collect prescribing information when controlled substances are dispensed, have varied substantially between states and over time. Little is known about the combinations of PDMP features that, collectively, may produce the greatest impact on prescribing and overdose. We aimed to (1) identify the types of PDMP models that have developed from 1999 to 2016, (2) estimate whether states have transitioned across PDMP models over time and (3) examine whether states have adopted different types of PDMP models in response to the burden of opioid overdose.

METHODS

A latent transition analysis of PDMP models based on an adaptation of nine PDMP characteristics classified by prescription opioid policy experts as potentially important determinants of prescribing practices and prescription opioid overdose events.

RESULTS

We divided the time-period into three intervals (1999-2004, 2005-09, 2010-16), and found three distinct PDMP classes in each interval. The classes in the first and second interval can be characterized as 'no/weak', 'proactive' and 'reactive' types of PDMPs, and in the third interval as 'weak', 'cooperative' and 'proactive'. The meaning of these classes changed over time: until 2009, states in the 'no/weak' class had no active PDMP, whereas states in the 'proactive' class were more likely to proactively provide unsolicited information to PDMP users, provide open access to law enforcement, and require more frequent data reporting than states in the 'reactive' class. In 2010-16, the 'weak' class resembled the 'reactive' class in previous intervals. States in the 'cooperative' class in 2010-16 were less likely than states in the 'proactive' class to provide unsolicited reports proactively or to provide open access to law enforcement; however, they were more likely than those in the 'proactive' class to share PDMP data with other states and to report more federal drug schedules.

CONCLUSIONS

Since 1999, US states have tended to transition to more robust classes of prescription drug monitoring programs. Opioid overdose deaths in prior years predicted the state's prescription drug monitoring program class but did not predict transitions between prescription drug monitoring program classes over time.

摘要

背景与目的

处方药物监测计划(PDMP)是指在美国使用的州级数据库,当管制物质被配药时,该数据库会收集处方信息。这些 PDMP 在各州之间以及随着时间的推移有很大的差异。关于可能对处方和过量使用产生最大影响的 PDMP 特征组合,人们知之甚少。我们的目的是:(1)确定 1999 年至 2016 年期间发展起来的 PDMP 模型类型;(2)估计各州是否随着时间的推移从一种 PDMP 模型过渡到另一种;(3)检查各州是否根据阿片类药物过量的负担采用不同类型的 PDMP 模型。

方法

基于处方阿片类药物政策专家将九个 PDMP 特征分类为可能对处方实践和处方阿片类药物过量事件有重要影响的潜在决定因素,对 PDMP 模型进行潜在转变分析。

结果

我们将这段时间分为三个区间(1999-2004 年、2005-09 年、2010-16 年),并在每个区间中发现了三种不同的 PDMP 类型。第一和第二个区间的类可以被描述为“无/弱”、“主动”和“被动”类型的 PDMP,而第三个区间的类则为“弱”、“合作”和“主动”。这些类别的含义随着时间的推移而变化:直到 2009 年,“无/弱”类别的州没有活跃的 PDMP,而“主动”类别的州更有可能主动向 PDMP 用户提供未请求的信息,向执法部门提供开放访问权限,并要求比“被动”类别的州更频繁地报告数据。在 2010-16 年,“弱”类类似于之前区间的“被动”类。2010-16 年的“合作”类州与“主动”类州相比,不太可能主动提供未请求的报告或向执法部门提供开放访问权限;然而,与“主动”类州相比,它们更有可能与其他州共享 PDMP 数据并报告更多的联邦药物时间表。

结论

自 1999 年以来,美国各州的处方药物监测计划趋于向更强大的类别发展。前几年的阿片类药物过量死亡预测了该州的处方药物监测计划类别,但并没有预测随着时间的推移在处方药物监测计划类别之间的转变。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7da/6314884/3b60e13916db/nihms-996012-f0001.jpg

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