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

质量决策的多机构实施：推动成果的临床决策支持分析工具

• 批准号: 10469309
• 负责人: Evan William Orenstein
• 金额: $ 85.79万
• 依托单位: PHRASE HEALTH, INC.
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-16 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10469309
• 关键词: Adoption; Advocate; Bundling; Caring; Child health care; Clinical; Clinical Practice Guideline; Clinical Trials; Clinical assessments; Computer software; Consolidated Framework for Implementation Research; Data; Development; Diagnosis; Diagnostic; Disease; Effectiveness; Electronic Health Record; Elements; Evaluation; Evidence based practice; Focus Groups; Future; Geographic Locations; Guidelines; Health; Health system; Hospitals; Hour; Incentives; Intervention; Interview; Knowledge; Knowledge Discovery; Lead; Measures; Meta-Analysis; Methods; Modeling; Outcome; Patient Care; Patient-Focused Outcomes; Patients; Pediatric Hospitals; Persons; Phase; Philadelphia; Physicians; Population; Process; Reach Effectiveness Adoption Implementation and Maintenance; Resources; Role; Running; Sepsis; Site; Software Design; Structure; Surveys; System; Therapeutic; Universities; Vermont; Work; analytical tool; base; clinical care; clinical decision support; cohort; community setting; dashboard; data exchange; design; experience; health care service organization; implementation barriers; implementation cost; implementation evaluation; implementation facilitators; implementation fidelity; implementation outcomes; implementation strategy; improved; improved outcome; insight; knowledge translation; meetings; mortality; novel; payment; phrases; primary outcome; process evaluation; prototype; research clinical testing; support tools; tool; usability

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.

项目总结/摘要 Phrase Health是一家临床决策支持（CDS）分析公司，它使卫生系统能够提供 通过CDS的数据驱动改进提供高价值的临床护理。CDS增强健康相关决策 以及与相关的、有组织的临床知识和患者信息相关的行动。例如，医生可能 很难记住所有指南推荐的脓毒症护理。通过订单集交付CDS 电子健康记录（EHR）中的可以通过捆绑 推荐的诊断和治疗顺序。然而，CDS可能无法改善结局 因为：（1）CDS工具未得到充分利用;（2）用户可能不遵循CDS推荐的操作; (3)建议的措施可能不会导致适当的循证实践（EBP）;和/或（4） EBP可能不会转化为新人群的预期结果。医疗机构需要一个 一种高效、严格且可扩展的过程评估方法，用于诊断CDS何时以及为何不会导致 预期的改进。在第一阶段，我们的团队展示了一种新的 软件产品，质量决策，指导所有经验水平的质量改进（QI）倡导者， (1)严格评估CDS对临床结局的影响，以及（2）将数据驱动的见解转化为行动。 在本第2阶段提案中，我们将使用RE-AIM框架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， 佛蒙特大学健康网络）。 在本提案的目标1中，我们将评估质量决策的实施效果。我们的首要 结果将是软件导致（1）新的QI或CDS干预的频率，（2） CDS有效性，或（3）队列或指标定义的变更。使用包括调查在内的混合方法， 日志数据和焦点小组，我们将评估实施效果，采用和保真度。我们亦会评估 实施的障碍和促进者使用的实施研究综合框架。 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。以试点 在第一阶段，每个卫生系统将为有限数量的CPG实施软件，并收集工作时间 安装和运行软件所需的所有数据。在扩展阶段，我们将估计机构数量 可以可行地纳入软件的CPG以及一年内实际构建的数量。 在这个项目结束时，我们将收集商业化我们的软件所需的主要数据， 潜在客户，包括（1）使用软件的客户资源需求描述 在卫生系统的CPG之间，以及（2）实施结果表明用户使用该软件 经常按计划进行，并获得有意义的见解。这些数据将为未来的客户展示价值 和投资者，使我们能够加速将知识转化为更好的健康成果。