Patient Entered Data for Clinical Decision Support to Personalize Pediatric Asthma Management

项目摘要/摘要 此K23，患者输入的数据用于临床决策支持，以个性化儿童哮喘管理，AIMS 通过加强、自动执行儿童哮喘指南来改善哮喘管理。 眼前的目标是获得技能和进一步的培训，以了解提供有效临床信息的方法。 哮喘管理的数学工具。应聘者是麻省理工学院小儿科助理教授 加州大学洛杉矶分校的儿科肺病学和临床信息学家。这位候选人已经召集了一场全国性的选举-- 经验丰富的指导团队，在定性研究、数据集成方面提供指导和专业知识 和实施学。培训计划结合定向课程作业，以加强这些方面的技能 以及与质量和卫生服务实施专家一起提供的教程，以获得必要的洞察力和 该项目所需的实践经验。职业培训包括专业发展研讨会、关键 科学会议，以及关于拨款撰写的课程工作，以优化未来的独立研究资金。 这项拟议的研究解决了从业者面临的挑战--目前还无法满足 纳入复杂的国家哮喘教育和预防计划(NAEPP)哮喘指南- 在他们的哮喘管理计划中。该研究利用患者输入的数据(通过患者门户)创建 一个全面的、自动生成的遵循指南的临床决策支持(CDS)工具。在组合中- 有了这些患者收集的数据，CDS工具将使用个人电子健康记录中的信息 (EHR)在护理时向医疗从业者推荐儿科哮喘管理计划。 关键的是，这项研究通过将患者报告的数据纳入到 信息收集工作流。以前在决策中使用患者门户的接受率很低，部分 由于可用性问题和临床工作流集成。现有的临床决策支持系统通常是 范围狭窄，没有纳入包括心理社会和环境在内的所有准则要素-- TAL因素。因此，本研究的具体目标是：1)开发和迭代提炼一个用户友好的 患者门户界面并评估其获取NAEPP指南关键要素的能力；2)开发 集成患者输入数据的综合CDS工具；以及3)试用CDS工具的捕获能力 临床环境中的指南要素。通过了解定性设计和用户体验设计 在开发阶段，我们计划推出一个无缝集成到最终用户任务(两个患者)中的CDS工具 和实践者)，帮助实践者执行全面的儿童哮喘管理计划 门诊部。R01申请，计划在本奖项的第四年提交，将对影响进行评估 使用RCT设计的患者门户/CDS工具。

PROJECT SUMMARY/ABSTRACT This K23, Patient Entered Data for Clinical Decision Support to Personalize Pediatric Asthma Management, aims to improve asthma management through enhanced, automated implementation of pediatric asthma guidelines. The immediate goal is to gain skills and further training to understand methods to deliver effective clinical infor- matics tools for asthma management. The candidate is an Assistant Professor of Pediatrics in the Division of Pediatric Pulmonology at UCLA and a clinical informaticist. The candidate has assembled a nationally recog- nized and experienced mentorship team to provide guidance and expertise in qualitative research, data integra- tion, and implementation science. The training plan combines directed coursework to strengthen skills in these areas; and tutorials with qualitative and health service implementation experts to gain the requisite insight and hands-on experience needed for this project. Career training includes professional development seminars, key scientific meetings, and coursework on grant writing to optimize future independent research funding. The proposed research addresses the challenge practitioners have – and are currently unable to meet – to incorporate the complex National Asthma Education and Prevention Program (NAEPP) asthma guideline ele- ments in their asthma management plan. This study leverages patient entered data (via a patient portal) to create a comprehensive, automatically generated guideline-adherent clinical decision support (CDS) tool. In combina- tion with this patient-collected data, the CDS tool will use information from the individual’s electronic health record (EHR) to recommend a pediatric asthma management plan to the healthcare practitioner at the point of care. Critically, this study advances asthma management in the EHR by incorporating patient-reported data into the information gathering workflow. Previous use of patient portals in decision-making has had low uptake, partially due to usability issues and clinical workflow integration. Existing clinical decision support systems are often of narrow scope and do not incorporate the entirety of guideline elements, including psychosocial and environmen- tal factors. As such, the specific aims for this research are: 1) to develop and iteratively refine a user-friendly patient portal interface and evaluate its ability to capture key elements of the NAEPP guideline; 2) to develop a comprehensive CDS tool that integrates patient entered data; and 3) to pilot the CDS tool’s ability to capture guideline elements in the clinical setting. By understanding qualitative and user experience design during the development phases, we plan to launch a CDS tool that integrates seamlessly into end user tasks (both patient and practitioner), helping practitioners execute a comprehensive asthma management plan for children in the outpatient setting. An R01 application, planned to be submitted in Year 4 of this award, will evaluate the impact of this patient portal/CDS tool using an RCT design.