Comparison of a national commercial pharmacy naloxone data source to state and city pharmacy naloxone data sources-Rhode Island, Massachusetts, and New York City, 2013-2019.

Autor: Chatterjee A; 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., Yan S; 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., Lambert A; 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., Morgan JR; Boston University School of Public Health, Boston, Massachusetts, USA., Green TC; The Heller School for Social Policy and Management, Brandeis University, Waltham, Massachusetts, USA., Jeng PJ; Department of Population Health Sciences, Weill Cornell Medical College, New York City, New York, USA., Jalali A; Department of Population Health Sciences, Weill Cornell Medical College, New York City, New York, USA., Xuan Z; Boston University School of Public Health, Boston, Massachusetts, USA., Krieger M; Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, USA., Marshall BDL; Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, USA., Walley AY; 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., Murphy SM; Department of Population Health Sciences, Weill Cornell Medical College, New York City, New York, USA.
Jazyk: angličtina
Zdroj: Health services research [Health Serv Res] 2023 Oct; Vol. 58 (5), pp. 1141-1150. Date of Electronic Publication: 2023 Jul 05.
DOI: 10.1111/1475-6773.14200
Abstrakt: Objective: 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).
Data Sources and Study Setting: 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).
Study Design: 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.
Principal Findings: 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.
Conclusions: 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.
(© 2023 Health Research and Educational Trust.)
Databáze: MEDLINE
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