Multi-Institutional Implementation of Quality Decisions: a Clinical Decision Support Analytics Tool to Drive Outcomes

项目摘要/摘要 Phrase Health是一家临床决策支持(CDS)分析公司，支持医疗系统提供 通过数据驱动的CDS改进实现高价值的临床护理。CDS加强与健康相关的决策 以及具有相关的、有组织的临床知识和患者信息的行动。例如，医生可能会 不记得订购所有指南推荐的脓毒症护理。通过订单集交付的CD 电子健康记录(EHR)可以简化这一过程，并通过捆绑 建议的诊断和治疗顺序一起。然而，CDS可能无法改善结果 因为：(1)CDS工具未得到充分利用；(2)用户可能没有遵循CDS的建议操作； (3)建议的行动可能不会导致适当的循证实践；及/或(4) 在新的人群中，EBP可能不会转化为预期的结果。医疗保健组织需要 高效、严格且可扩展的流程评估方法，可诊断CDS何时以及为什么不会导致 预期的改进。在第一阶段，我们的团队展示了新的 软件产品、质量决策，引导所有经验级别的质量改进(QI)倡导者 (1)严格评估CDS对临床结果的影响；(2)将数据驱动的见解转化为行动。 在此阶段2提案中，我们将使用RE-AIM框架来评估质量决策的实施情况 三个不同的卫生系统(亚特兰大儿童保健、费城儿童医院和 佛蒙特州大学健康网络)。 在本提案的目标1中，我们将评估质量决定的实施效果。我们的初选 结果将是软件导致(1)新的QI或CDS干预(S)的频率，(2)增加对 CDS有效性，或(3)队列或测量定义的变化。使用包括调查在内的混合方法， 日志数据和焦点小组，我们将评估实施效率、采用率和保真度。我们还将评估 使用实施研究综合框架的实施障碍和促进者。 在目标2中，我们将确定大规模实施质量决策所需的客户资源。在试行中 在这一阶段，每个保健系统将为有限数量的CPG实施该软件，并收集工作时间 启动和运行软件所需的。在扩展阶段，我们将估计机构的数量 可以可行地将CPG整合到软件中，并在一年内实际构建的数量。 在这个项目结束时，我们将收集到将我们的软件商业化所需的主要数据 潜在客户包括(1)使用软件所需的客户资源描述 跨保健系统中的CPG和(2)显示用户使用该软件的实施结果 经常按照预期进行，并获得有意义的见解。这些数据将展示未来客户运营的价值 和投资者，使我们能够加快将知识转化为更好的健康结果。

Project Summary/Abstract Phrase Health is a clinical decision support (CDS) analytics company that empowers health systems to deliver high value clinical care through data-driven improvements of CDS. CDS enhances health‐related decisions and actions with pertinent, organized clinical knowledge, and patient information. For example, physicians may have trouble remembering to order all guideline-recommended care for sepsis. CDS delivered via an order set in the electronic health record (EHR) can simplify this process and reduce mortality by bundling the recommended diagnostic and therapeutic orders together. However, CDS may fail to improve outcomes because: (1) the CDS tool is underutilized; (2) the user may not follow the recommended action from the CDS; (3) the recommended action may not lead to the appropriate evidence-based practice (EBP); and/or (4) the EBP may not translate to the expected outcome in a novel population. Healthcare organizations need an efficient, rigorous, and scalable process evaluation method to diagnose when and why CDS is not leading to the intended improvements. In Phase 1, our team demonstrated the technical feasibility and usability of a new software product, Quality Decisions, that guides quality improvement (QI) advocates of all experience levels to (1) rigorously evaluate the impact of CDS on clinical outcomes and (2) convert data-driven insights into action. In this Phase 2 proposal, we will use the RE-AIM framework to evaluate implementation of Quality Decisions at three diverse health systems (Children’s Healthcare of Atlanta, Children’s Hospital of Philadelphia, and The University of Vermont Health Network). In Aim 1 of this proposal, we will evaluate the implementation effectiveness of Quality Decisions. Our primary outcome will be how often the software leads to (1) new QI or CDS intervention(s), (2) increased confidence in CDS effectiveness, or (3) changes in cohort or measure definitions. Using mixed methods including surveys, log data, and focus groups, we will evaluate implementation efficacy, adoption, and fidelity. We will also assess implementation barriers and facilitators using the Consolidated Framework for Implementation Research. In Aim 2, we will determine the customer resources required to implement Quality Decisions at scale. In a pilot phase, each health system will implement the software for a limited number of CPGs and collect hours of work required to get the software up and running. In an expansion phase, we will estimate the number of institutional CPGs that could feasibly be incorporated into the software and the number actually built in one year. At the end of this project, we will have collected the primary data required to commercialize our software to potential customers including (1) a description of the customer resource requirements to use the software across CPGs in a health system and (2) implementation outcomes demonstrating that users use the software frequently as intended and gain meaningful insights. These data will demonstrate value for future cust omers and investors, allowing us accelerate the translation of knowledge into better health outcomes.