背景:处方阿片类药物仍然是美国阿片类药物危机和阿片类药物使用障碍的重要原因。最近的立法行动,如实施国家处方药监测计划(PDMPs),旨在通过加强处方数据的跟踪和报告来降低阿片类药物的发病率和死亡率。我们研究的主要目的是描述PAPDMP在报告指南立法变化后记录的宾夕法尼亚州(PA)的阿片类药物处方趋势。并讨论了PDMP在减少阿片类药物危害的多因素方法中的作用。
方法:从PA卫生部收集了PAPDMP从2016年8月至2020年3月每个日历季度记录的州级阿片类药物处方数据摘要。羟考酮的数据,氢可酮,和吗啡按季度分析总处方数量和补充剂量。处方长度,药丸数量,按季度分析了PAPDMP记录的所有14种阿片类药物处方变体的平均吗啡毫当量(MME).对每组变量进行线性回归,以确定处方趋势的显着差异。
结果:对于分配的总处方,羟考酮的数量,氢可酮,和吗啡处方分别下降了34.4、44.6和22.3%(p<0.0001)。回填与2017年第三季度和2018年第三季度的一般峰值波动不一致(p=0.2878)。所有阿片类药物处方长度的处方率下降,使用阿片类药物的频率为22至30天(占处方的47.5%)至31天以上(占处方的0.8%)(p<0.0001)。同样,所有处方量都观察到处方减少,频率从22到60粒(占处方的36.6%)到60-90粒(占处方的14.2%)(p<0.0001)。总的来说,每个阿片类药物处方的平均MME减少了18.9%.
结论:根据PAPDMP数据库,从2016年到2020年,PA的阿片类药物处方大幅下降。PDMP数据库是追踪PA阿片类药物处方趋势的重要工具,和PDMPs在其他州类似的结构可能会增强我们理解和影响美国阿片类药物危机轨迹的能力。需要进一步研究以确定全国范围内的最佳PDMP政策和实践。
BACKGROUND: Prescription opioids remain an important contributor to the United States opioid crisis and to the development of opioid use disorder for opioid-naïve individuals. Recent legislative actions, such as the implementation of state prescription drug monitoring programs (PDMPs), aim to reduce opioid morbidity and mortality through enhanced tracking and reporting of prescription data. The primary objective of our study was to describe the opioid prescribing trends in the state of Pennsylvania (PA) as recorded by the PA
PDMP following legislative changes in reporting guidelines, and discuss the
PDMP\'s role in a multifactorial approach to opioid harm reduction.
METHODS: State-level opioid prescription data summaries recorded by the PA
PDMP for each calendar quarter from August 2016 through March 2020 were collected from the PA Department of Health. Data for oxycodone, hydrocodone, and morphine were analyzed by quarter for total prescription numbers and refills. Prescription lengths, pill quantities, and average morphine milliequivalents (MMEs) were analyzed by quarter for all 14 opioid prescription variants recorded by the PA PDMP. Linear regression was conducted for each group of variables to identify significant differences in prescribing trends.
RESULTS: For total prescriptions dispensed, the number of oxycodone, hydrocodone, and morphine prescriptions decreased by 34.4, 44.6, and 22.3% respectively (p < 0.0001). Refills fluctuated less consistently with general peaks in Q3 of 2017 and Q3 of 2018 (p = 0.2878). The rate of prescribing for all opioid prescription lengths decreased, ranging in frequency from 22 to 30 days (47.5% of prescriptions) to 31+ days of opioids (0.8% of prescriptions) (p < 0.0001). Similarly, decreased prescribing was observed for all prescription amounts, ranging in frequency from 22 to 60 pills (36.6% of prescriptions) to 60-90 pills (14.2% of prescriptions) (p < 0.0001). Overall, the average MME per opioid prescription decreased by 18.9%.
CONCLUSIONS: Per the PA
PDMP database, opioid prescribing has decreased significantly in PA from 2016 to 2020. The PDMP database is an important tool for tracking opioid prescribing trends in PA, and PDMPs structured similarly in other states may enhance our ability to understand and influence the trajectory of the U.S. opioid crisis. Further research is needed to determine optimal
PDMP policies and practices nationwide.