Improving pain management and opioid safety through a systemwide, data driven evaluation of the CDC opioid prescribing guideline best practices and the use of Clinical Decision Support

项目摘要 有效治疗疼痛，同时安全地开出阿片类止痛药是公共卫生的优先事项。 CDC阿片类药物处方指南是减少不必要阿片类药物的循证方法 暴露、高风险阿片类药物的使用和滥用。2016年的版本有一些小的改进，但 有时被误用于不安全的阿片类药物逐渐减少；突出了实施和 更改提供程序行为。随着指南预计将很快更新，有必要进行前瞻性试验 确定战略，以高效和有效地交付疾控中心指南建议的做法，同时 记录它们对以患者为中心的结果的影响(例如，疼痛控制、发病率和死亡率)。 临床决策支持(CDS)是一种既可操作又可操作的有前途的实施策略 以证据为基础的做法，最大限度地发挥例行收集的数据的价值。我们将使用电子设备 健康记录(EHR)嵌入CDS以修改临床行为以符合CDC指南 建议。我们提出了一种混合有效性-实施试验，使用Accept 实施科学框架PRISM(实用、稳健的实施和可持续发展模式) 和RE-AIM(覆盖范围、有效性、采用、实施和维护)来考虑 影响实施成功的多层次背景因素。通过开发数据驱动的 具有通过链接到处方来评估患者结果的能力的学习卫生系统 药物监测计划、保险索赔和死亡数据，该项目将评估： (1)描述疾病预防控制中心指南-一致性处方的有效性 指导方针协调一致的行动和患者结果。 (2)基于EHR的CDS以用户为中心的设计，以促进CDC指南的协调行动和 推广疼痛管理的非阿片类药物方法。 (3)对CDS战略的实施和有效性的评价，以交付指导方针- 在一个大型综合卫生系统中进行的务实分组随机试验中的一致性护理。我们会 系统评估关键实施成果，然后评估CDS在以下方面的有效性 患者结局(与常规护理相比)。 这项务实的研究将解决将提供者的处方行为与个人联系起来的需要 病人的结果。使用既定的实施科学方法将CDS作为 实施战略具有创新性和重要性。我们的结果将为文档记录提供可靠的数据 CDC指南一致性处方的有效性和评估一个新兴的、可扩展的 执行战略，利用现有数据减少阿片类药物危机的发病率和死亡率。

Project Summary Effectively treating pain while safely prescribing opioid pain medicines is a public health priority. The CDC opioid prescribing guidelines are an evidence-based approach to decreasing unnecessary opioid exposures, high-risk opioid use and abuse. The 2016 version produced modest improvements, but were sometimes misapplied for unsafe opioid tapering; highlighting the challenges of implementation and changing provider behavior. With guideline updates expected soon, there is a need for prospective trials to identify strategies to efficiently and effectively deliver CDC guideline recommended practices while documenting their impact on patient centered outcomes (e.g., pain control, morbidity and mortality). Clinical decision support (CDS) is a promising implementation strategy to both operationalize evidence-based practices and maximize the value of routinely collected data. We will use electronic health record (EHR) embedded CDS to modify clinical behavior toward CDC guideline-concordant recommendations. We propose a hybrid effectiveness-implementation trial using accepted implementation science frameworks PRISM (Practical, Robust Implementation and Sustainability Model) and RE-AIM (Reach, Effectiveness, Adoption, Implementation and Maintenance) to consider the multilevel contextual factors that influence implementation success. By developing a data-driven learning health system with the ability to evaluate patient outcomes through linkages to Prescription Drug Monitoring Program, insurance claims and death data, this project will evaluate: (1) The effectiveness of CDC guideline-concordant prescribing by describing the association between guideline concordant actions and patient outcomes. (2) The user-centered design of EHR based CDS to facilitate CDC guideline concordant actions and promote non-opioid approaches to pain management. (3) The evaluation of the implementation and effectiveness of CDS strategies to deliver guideline- concordant care in a pragmatic cluster randomized trial in a large, integrated health system. We will systematically assess key implementation outcomes and then evaluate the effectiveness of CDS on patient outcomes (vs usual care). This pragmatic research will address the need to link provider prescribing actions to individual patient outcomes. Using established implementation science approaches to evaluate CDS as an implementation strategy is innovative and important. Our results will provide robust data to document the effectiveness of CDC guideline concordant prescribing and evaluate an emerging, scalable implementation strategy using existing data to decrease morbidity and mortality from the opioid crisis.