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

患者输入数据用于临床决策支持，以个性化小儿哮喘管理

• 批准号: 9977303
• 负责人: Mindy K Ross
• 金额: $ 19.6万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-15 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9977303
• 关键词: 11 year old; Address; Adherence; Algorithms; Area; Asthma; Award; Caregivers; Caring; Child; Childhood; Childhood Asthma; Chiroptera; Clinic Visits; Clinical; Clinical Data; Clinical Decision Support Systems; Clinical Informatics; Clinical Trials; Complex; Data; Data Reporting; Decision Making; Development; Education; Electronic Health Record; Elements; Environment; Environmental Risk Factor; Family; Funding; Future; General Practitioners; Goals; Grant; Guidelines; Health Services; Health system; Healthcare; Hospitalization; Individual; Informatics; Information Technology; Knowledge; Manuals; Measures; Mentorship; Methods; Outcome; Outpatients; Parents; Patient Care; Patient Outcomes Assessments; Patients; Pediatrics; Pharmaceutical Preparations; Pharmacotherapy; Phase; Physicians; Prevention program; Process; Productivity; Proxy; Psychosocial Factor; Publishing; Pulmonology; Qualitative Methods; Qualitative Research; Questionnaires; Reporting; Research; Risk Factors; Severities; Social Environment; Socioeconomic Status; Specialist; Standardization; Symptoms; System; Target Populations; Testing; Time; Training; United States National Institutes of Health; Visit; Work; Writing; age group; asthmatic patient; base; care outcomes; career; clinical decision support; clinical decision-making; comorbidity; computerized; data integration; design; experience; implementation science; improved; informatics tool; information gathering; insight; low socioeconomic status; medication compliance; meetings; patient portal; pediatrician; point of care; professor; skills; stressor; support tools; tool; treatment as usual; uptake; usability; user-friendly

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.

项目总结/摘要 这K23，患者输入数据的临床决策支持，以个性化儿科哮喘管理，目的是 通过增强、自动化实施儿科哮喘指南来改善哮喘管理。 近期目标是获得技能和进一步培训，以了解提供有效临床信息的方法。 用于哮喘管理的matics工具。候选人是儿科学助理教授， 加州大学洛杉矶分校的儿科和临床信息学家。这位候选人召集了一个全国性的会议， 专业的、经验丰富的导师团队，在定性研究、数据整合、 和执行科学。培训计划结合了指导性的课程，以加强这些技能， 领域;以及与定性和卫生服务实施专家的教程，以获得必要的洞察力， 实践经验需要这个项目。职业培训包括专业发展研讨会， 科学会议，以及关于资助写作的课程，以优化未来的独立研究资金。 拟议的研究解决了从业者面临的挑战-目前无法满足- 将复杂的国家哮喘教育和预防计划（NAEPP）哮喘指南纳入其中， 哮喘管理计划中。本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- 与此患者收集的数据，CDS工具将使用来自个人的电子健康记录的信息 (EHR)建议一个儿科哮喘管理计划，以保健医生在护理点。 重要的是，这项研究通过将患者报告的数据纳入EHR中， 信息收集工作流程。以前在决策中使用患者门户网站的比例很低，部分原因是 由于可用性问题和临床工作流程集成。现有的临床决策支持系统通常 范围狭窄，没有纳入全部准则内容，包括社会心理和职业道德， 谈话因素。因此，本研究的具体目标是：1）开发和迭代完善用户友好的 患者门户接口，并评估其捕获NAEPP指南关键要素的能力; 2）开发 整合患者输入数据的综合CDS工具;以及3）试验CDS工具捕获 临床环境中的指南要素。通过理解定性和用户体验设计， 在开发阶段，我们计划推出一个CDS工具，该工具可以无缝集成到最终用户任务（包括患者 和医生），帮助医生执行一个全面的哮喘管理计划，为儿童在 门诊设置。R 01应用程序，计划在今年提交本奖项的4，将评估影响 使用RCT设计的患者门户/CDS工具。