Dual Use of Medications (DUAL) Partnered Evaluation Initiative

药物双重用途 (DUAL) 合作评估计划

基本信息

  • 批准号:
    10181835
  • 负责人:
  • 金额:
    --
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-01-01 至 2023-12-31
  • 项目状态:
    已结题

项目摘要

The VA Center for Medication Safety (VAMedSAFE) is charged with improving the safety of medication use for Veterans. VAMedSAFE’s interventions address the most serious, prevalent, and high-priority health conditions among Veterans, and yet they have a key limitation – they cannot account for medications received by Veterans outside VA. Over 80% of VA enrollees have access to medications through other forms of health insurance, including 50% with Medicare. There is strong evidence that receiving medications from multiple health systems poses serious health risks. The inability to integrate non-VA prescriptions into VA medication surveillance efforts has greatly diminished VA’s capacity to ensure safe prescribing to Veterans. Driven by this evidence, VA signed a groundbreaking agreement with the Centers for Medicare & Medicaid Services (CMS) to integrate CMS data on prescriptions filled by Veterans in Medicare into VAMedSAFE’s ongoing safety surveillance activities – something VA has never before been able to do. By the end of calendar year 2020, VAMedSAFE will have received and cleaned CMS data on dispensed Medicare prescriptions for all enrolled Veterans and will integrate these data into their ongoing medication surveillance activities. The objective of our proposed Dual Use of Medications (DUAL) Partnered Evaluation Initiative is to aid VAMedSAFE in developing and evaluating the roll-out of new quality enhancement tools using these combined CMS/VA data. Our evaluation has three aims, with the first aim split into two sub-aims. In Aim 1, we will work with VAMedSAFE to formatively evaluate the types of medications to prioritize when integrating CMS prescription data into their quality enhancement tools. Aim 1a will quantify how the integration of CMS prescription data could impact exposure measurement (e.g., number of patients identified as incident medication users) and outcomes (e.g., number of patients with a medication-related adverse event) for each ongoing VAMedSAFE surveillance program. Aim 1b will identify high-impact targets for new VA drug safety initiatives using CMS/VA data, using both quantitative and qualitative analyses. We will query the CMS/VA data to identify broad drug classes (e.g., hypoglycemics, opioids) that are frequently duplicated or overlapping between CMS and VA. Then, we will convene two interdisciplinary focus groups with key stakeholders to identify additional potential high-impact drug targets for future interventions using the CMS/VA data. In Aim 2, we will evaluate end users’ experiences with the first integration of CMS data into a VAMedSAFE drug safety dashboard focusing on direct-acting oral anticoagulant safety. Guided by the Practical, Robust Implementation and Sustainability Model (PRISM), we will conduct telephone interviews with end users of the dashboard (e.g., pharmacy directors, academic detailers, clinicians) to identify implementation barriers and facilitators and learn about their experiences receiving the data, how it impacts clinical care, and whether CMS data integration leads to unintended consequences. Finally, in Aim 3, we will partner with VAMedSAFE to design and deploy a stepped-wedge randomized evaluation of a 2nd drug safety dashboard using integrated CMS and VA data, using findings from Aims 1 and 2 to identify the optimal drug target and implementation support. We will use RE-AIM as a framework for examining effectiveness (e.g., drug discontinuation, adverse events) and implementation (e.g. reach, adoption) outcomes. These new data provide an unprecedented opportunity to strengthen VA medication safety surveillance for Veterans who receive medications through Medicare. This evaluation was requested and is co-funded by VAMedSAFE, which requires a non-research partnership, as the CMS/VA data can only be used for quality improvement. This project aligns with VA QUERI priorities to apply implementation science to real-world practices, use novel data sources for quality improvement, and help program offices build data capacity and evaluate new quality enhancement tools.
VA药物安全中心(VAMedSAFE)负责提高药物使用的安全性

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Walid F. Gellad其他文献

Active surveillance pharmacovigilance for emClostridioides difficile/em infection and gastrointestinal bleeding: an analytic framework based on case-control studies
艰难梭菌感染和胃肠道出血的主动监测药物警戒:基于病例对照研究的分析框架
  • DOI:
    10.1016/j.ebiom.2024.105130
  • 发表时间:
    2024-05-01
  • 期刊:
  • 影响因子:
    10.800
  • 作者:
    Ravy K. Vajravelu;Amy R. Byerly;Robert Feldman;Scott D. Rothenberger;Robert E. Schoen;Walid F. Gellad;James D. Lewis
  • 通讯作者:
    James D. Lewis
The Veterans Choice Act and Dual Health System Use
Temporal Trends in Opioid-Related Care and Pain Among Veterans at the End of Life
退伍军人临终时与阿片类药物相关护理和疼痛的时间趋势
  • DOI:
    10.1016/j.jpainsymman.2025.03.032
  • 发表时间:
    2025-07-01
  • 期刊:
  • 影响因子:
    3.500
  • 作者:
    Melissa W. Wachterman;Stuart R. Lipsitz;Erin Beilstein-Wedel;Walid F. Gellad;Karl A. Lorenz;Nancy L. Keating
  • 通讯作者:
    Nancy L. Keating
Marked Increase in Sales of Erectile Dysfunction Medication During COVID-19
  • DOI:
    10.1007/s11606-021-06968-2
  • 发表时间:
    2021-06-25
  • 期刊:
  • 影响因子:
    4.200
  • 作者:
    Inmaculada Hernandez;Zeynep Gul;Walid F. Gellad;Benjamin J. Davies
  • 通讯作者:
    Benjamin J. Davies
Maximierung der Sicherheit von Flibanserin: Die Rolle von Aufsichtsbehörden, Klinikern und Patientinnen
Flibanserin 的最大安全:Die Rolle von Aufsichtsbehörden、Klinikern und Patientinnen
  • DOI:
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sheriza N. Baksh;Walid F. Gellad;G. Alexander
  • 通讯作者:
    G. Alexander

Walid F. Gellad的其他文献

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{{ truncateString('Walid F. Gellad', 18)}}的其他基金

Leveraging a natural experiment to identify the effects of VA community care programs on health care quality, equity, and Veteran experiences
利用自然实验来确定 VA 社区护理计划对医疗保健质量、公平性和退伍军人体验的影响
  • 批准号:
    10595577
  • 财政年份:
    2022
  • 资助金额:
    --
  • 项目类别:
STORM Implementation Program Evaluation
STORM实施计划评估
  • 批准号:
    9568349
  • 财政年份:
    2017
  • 资助金额:
    --
  • 项目类别:
Machine-Learning Prediction and Reducing Overdoses with EHR Nudges (mPROVEN)
机器学习预测并通过 EHR 推动减少用药过量 (mPROVEN)
  • 批准号:
    10641919
  • 财政年份:
    2017
  • 资助金额:
    --
  • 项目类别:
Using Machine Learning to Predict Problematic Prescription Opioid Use and Opioid Overdose
使用机器学习来预测有问题的处方阿片类药物使用和阿片类药物过量
  • 批准号:
    9421755
  • 财政年份:
    2017
  • 资助金额:
    --
  • 项目类别:
Safety of Opioid use Among Veterans Receiving Care in Multiple Health Systems
在多个卫生系统接受护理的退伍军人使用阿片类药物的安全性
  • 批准号:
    9015268
  • 财政年份:
    2015
  • 资助金额:
    --
  • 项目类别:
Safety of Opioid use Among Veterans Receiving Care in Multiple Health Systems
在多个卫生系统接受护理的退伍军人使用阿片类药物的安全性
  • 批准号:
    9888304
  • 财政年份:
    2015
  • 资助金额:
    --
  • 项目类别:

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