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Trends in stimulant dispensing by age, sex, state of residence, and prescriber specialty - United States, 2014-2019.2014-2019 年美国按年龄、性别、居住州和开处方医生专业划分的兴奋剂配药趋势。
Drug Alcohol Depend. 2020 Dec 1;217:108297. doi: 10.1016/j.drugalcdep.2020.108297. Epub 2020 Sep 15.
2
Drug Overdose Deaths in the United States, 1999-2018.美国 1999-2018 年药物过量死亡人数。
NCHS Data Brief. 2020 Jan(356):1-8.
3
Drug and Opioid-Involved Overdose Deaths - United States, 2017-2018.药物和阿片类药物相关过量死亡 - 美国,2017-2018 年。
MMWR Morb Mortal Wkly Rep. 2020 Mar 20;69(11):290-297. doi: 10.15585/mmwr.mm6911a4.
4
The rise in non-fatal and fatal overdoses involving stimulants with and without opioids in the United States.美国涉及兴奋剂(有和没有阿片类药物)的非致命和致命过量用药的上升。
Addiction. 2020 May;115(5):946-958. doi: 10.1111/add.14878. Epub 2020 Jan 7.
5
The epidemiology of benzodiazepine misuse: A systematic review.苯二氮䓬类药物滥用的流行病学:系统评价。
Drug Alcohol Depend. 2019 Jul 1;200:95-114. doi: 10.1016/j.drugalcdep.2019.02.033. Epub 2019 May 7.
6
Initial Opioid Prescriptions among U.S. Commercially Insured Patients, 2012-2017.2012-2017 年美国商业保险患者初始阿片类药物处方情况。
N Engl J Med. 2019 Mar 14;380(11):1043-1052. doi: 10.1056/NEJMsa1807069.
7
County-Level Opioid Prescribing in the United States, 2015 and 2017.美国 2015 年和 2017 年县级阿片类药物处方情况
JAMA Intern Med. 2019 Apr 1;179(4):574-576. doi: 10.1001/jamainternmed.2018.6989.
8
Polysubstance Use by Stimulant Users: Health Outcomes Over Three Years.兴奋剂使用者的多物质使用:三年健康结果。
J Stud Alcohol Drugs. 2018 Sep;79(5):799-807. doi: 10.15288/jsad.2018.79.799.
9
Prescription fill rates for acute and chronic medications in claims-EMR linked data.索赔-电子病历关联数据中急性和慢性药物的处方填充率。
Medicine (Baltimore). 2018 Nov;97(44):e13110. doi: 10.1097/MD.0000000000013110.
10
Potentially Inappropriate Opioid Prescribing, Overdose, and Mortality in Massachusetts, 2011-2015.2011-2015 年马萨诸塞州潜在不适当阿片类药物处方、用药过量和死亡率。
J Gen Intern Med. 2018 Sep;33(9):1512-1519. doi: 10.1007/s11606-018-4532-5. Epub 2018 Jun 14.

利用电子病历和理赔数据评估阿片类药物处方与配药的一致性。

Congruence of opioid prescriptions and dispensing using electronic records and claims data.

机构信息

Division of Overdose Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.

出版信息

Health Serv Res. 2021 Dec;56(6):1245-1251. doi: 10.1111/1475-6773.13673. Epub 2021 May 18.

DOI:10.1111/1475-6773.13673
PMID:34008209
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8586485/
Abstract

OBJECTIVE

To quantify discrepancies between opioid prescribing and dispensing via the percentage of patients with Electronic Medical Record (EMR) prescriptions who subsequently filled the prescription within 90 days, defined as congruence, and compared opioid congruence with related medications.

DATA SOURCES

Deidentified data from the IBM MarketScan Explorys Claims-EMR Dataset.

STUDY DESIGN

In this retrospective, observational study, we examined congruence for commonly prescribed controlled substances-opioids, stimulants, and benzodiazepines. Congruence was stratified by age group and sex.

DATA COLLECTION/EXTRACTION METHODS: Continuously enrolled adults aged 18-64 years with an EMR encounter (excluding inpatient settings) and ≥ 1 prescription for selected classes between 1/1/2016 and 10/2/2017.

PRINCIPAL FINDINGS

During the study period, 1,353,478 adults had ≥1 EMR encounter. Patients with stimulants prescriptions had the highest congruence (83%) corresponding to 7151 claims for 8,635 EMR prescriptions, followed by opioids (66%; 62,766/95,690) and benzodiazepines (64%; 30,181/47,408). Chi-square testing showed congruence differed by age group within opioids (P < .0001) and benzodiazepines (P < .0001) and was higher among females within benzodiazepines (P < .0001).

CONCLUSIONS

These findings demonstrate that relying on claims data alone for opioid prescribing measures might underestimate actual prescribing magnitude by as much as one-third in these data. Combined EMR and claims data can help future research better understand characteristics associated with congruence or incongruence between prescribing and dispensing.

摘要

目的

通过电子病历 (EMR) 处方中随后在 90 天内填写处方的患者比例(定义为一致性)量化阿片类药物处方与配药之间的差异,并将阿片类药物一致性与相关药物进行比较。

数据来源

来自 IBM MarketScan Explorys Claims-EMR 数据集的匿名数据。

研究设计

在这项回顾性观察研究中,我们检查了常用受控物质 - 阿片类药物、兴奋剂和苯二氮䓬类药物的一致性。一致性按年龄组和性别分层。

数据收集/提取方法:连续招募年龄在 18-64 岁之间的成年人,他们在 1/1/2016 至 10/2/2017 期间至少有一次 EMR 就诊(不包括住院环境)和至少有一次选定类别的处方。

主要发现

在研究期间,1353478 名成年人至少有一次 EMR 就诊。使用兴奋剂处方的患者一致性最高(83%),对应 7151 份索赔和 95690 份 EMR 处方中的 8635 份,其次是阿片类药物(66%;62766/95690)和苯二氮䓬类药物(64%;30181/47408)。卡方检验显示,阿片类药物和苯二氮䓬类药物的年龄组之间的一致性存在差异(P<.0001),苯二氮䓬类药物中女性的一致性更高(P<.0001)。

结论

这些发现表明,仅依靠索赔数据来衡量阿片类药物的处方措施可能会低估这些数据中实际处方的幅度,多达三分之一。EMR 和索赔数据的结合可以帮助未来的研究更好地了解与处方和配药之间一致性或不一致性相关的特征。