Grayken Center for Addiction, Clinical Addiction Research and Education Unit, Section of General Internal Medicine, Boston Medical Center/Boston University School of Medicine, Boston, Massachusetts, USA.
Boston University School of Public Health, Boston, Massachusetts, USA.
Health Serv Res. 2023 Oct;58(5):1141-1150. doi: 10.1111/1475-6773.14200. Epub 2023 Jul 5.
Accurate naloxone distribution data are critical for planning and prevention purposes, yet sources of naloxone dispensing data vary by location, and completeness of local datasets is unknown. We sought to compare available datasets in Massachusetts, Rhode Island, and New York City (NYC) to a commercially available pharmacy national claims dataset (Symphony Health Solutions).
We utilized retail pharmacy naloxone dispensing data from NYC (2018-2019), Rhode Island (2013-2019), and Massachusetts (2014-2018), and pharmaceutical claims data from Symphony Health Solutions (2013-2019).
We conducted a descriptive, retrospective, and secondary analysis comparing naloxone dispensing events (NDEs) captured via Symphony to NDEs captured by local datasets from the three jurisdictions between 2013 and 2019, when data were available from both sources, using descriptive statistics, regressions, and heat maps.
DATA COLLECTION/EXTRACTION METHODS: We defined an NDE as a dispensing event documented by the pharmacy and assumed that each dispensing event represented one naloxone kit (i.e., two doses). We extracted NDEs from local datasets and the Symphony claims dataset. The unit of analysis was the ZIP Code annual quarter.
NDEs captured by Symphony exceeded those in local datasets for each time period and location, except in RI following legislation requiring NDEs to be reported to the PDMP. In regression analysis, absolute differences in NDEs between datasets increased substantially over time, except in RI before the PDMP. Heat maps of NDEs by ZIP code quarter showed important variations reflecting where pharmacies may not be reporting NDEs to Symphony or local datasets.
Policymakers must be able to monitor the quantity and location of NDEs in order to combat the opioid crisis. In regions where NDEs are not required to be reported to PDMPs, proprietary pharmaceutical claims datasets may be useful alternatives, with a need for local expertise to assess dataset-specific variability.
准确的纳洛酮分发数据对于规划和预防目的至关重要,但纳洛酮配药数据的来源因地点而异,并且局部数据集的完整性尚不清楚。我们试图将马萨诸塞州、罗得岛州和纽约市(NYC)的现有数据集与商业可用的药房全国索赔数据集(Symphony Health Solutions)进行比较。
我们利用了纽约市(2018-2019 年)、罗得岛州(2013-2019 年)和马萨诸塞州(2014-2018 年)的零售药房纳洛酮配药数据,以及 Symphony Health Solutions 的药品索赔数据(2013-2019 年)。
我们进行了描述性、回顾性和二次分析,比较了 2013 年至 2019 年期间 Symphony 捕捉到的纳洛酮配药事件(NDE)与三个司法管辖区的本地数据集捕捉到的 NDE,使用描述性统计、回归和热图。
数据收集/提取方法:我们将 NDE 定义为药房记录的配药事件,并假定每次配药事件代表一个纳洛酮试剂盒(即两剂)。我们从本地数据集和 Symphony 索赔数据集中提取 NDE。分析单位是邮政编码年度季度。
除了在罗得岛州,在立法要求将 NDE 报告给 PDMP 之后,每个时间段和地点,Symphony 捕捉到的 NDE 都超过了本地数据集。在回归分析中,数据集之间 NDE 的绝对差异随着时间的推移大大增加,除了在 PDMP 之前的罗得岛州。按邮政编码季度划分的 NDE 热图显示了重要的差异,反映了药店可能没有向 Symphony 或本地数据集报告 NDE 的地方。
政策制定者必须能够监测 NDE 的数量和位置,以便应对阿片类药物危机。在不需要向 PDMP 报告 NDE 的地区,专有药品索赔数据集可能是有用的替代方案,需要当地专业知识来评估数据集特定的可变性。