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来源类型Working Paper
规范类型报告
DOI10.3386/w24947
来源IDWorking Paper 24947
The Problem of Data Quality in Analyses of Opioid Regulation: The Case of Prescription Drug Monitoring Programs
Jill Horwitz; Corey S. Davis; Lynn S. McClelland; Rebecca S. Fordon; Ellen Meara
发表日期2018-09-03
出版年2018
语种英语
摘要States, which have the primary legal role in regulating the prescribing and dispensing of prescription medications, have created Prescription Drug Monitoring Programs (PDMP) to try to reduce inappropriate prescribing, dispensing, and related harm. Research assessing whether these interventions are effective has produced inconclusive and contradictory results. Here we examine whether different data sources may have contributed to the varying results. Specifically, we: 1) identify the decisions inherent in creating such a dataset; 2) discuss the public data sources used by researchers in previous work; 3) develop and apply a detailed research protocol to create a novel PDMP law dataset; and 4) to illustrate potential consequences of data choice, apply various data sources to analyze the relationship between PDMP laws and prescribing and dispensing of opioids among disabled Medicare beneficiaries. We find that our dates differ from those in existing datasets, sometimes by many years. The regression analyses generated a twofold difference in point estimates, as well as different signed estimates, depending on the data used. We conclude that the lack of transparency about data assembly in existing datasets, differences among dates by source, and the regression results raise concerns for PDMP researchers and policymakers.
主题Health, Education, and Welfare ; Health ; Other ; Law and Economics
URLhttps://www.nber.org/papers/w24947
来源智库National Bureau of Economic Research (United States)
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条目标识符http://119.78.100.153/handle/2XGU8XDN/582621
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Jill Horwitz,Corey S. Davis,Lynn S. McClelland,et al. The Problem of Data Quality in Analyses of Opioid Regulation: The Case of Prescription Drug Monitoring Programs. 2018.
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