Improving Glaucoma Care Using a Scalable Decision Support System

使用可扩展的决策支持系统改善青光眼护理

• 批准号: 10615141
• 负责人: Brian Stagg
• 金额: $ 27.02万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10615141
• 关键词: Address; Affect; Biometry; Blindness; Caring; Characteristics; Chronic; Chronic Disease; Clinic; Clinical; Clinical Decision Support Systems; Clinical effectiveness; Cognitive; Complex; Country; Data; Data Science; Data Sources; Decision Making; Decision Support Systems; Development; Development Plans; Early identification; Environment; Ethnography; Evaluation; Eye; Eye diseases; Face; Fast Healthcare Interoperability Resources; Fellowship; Frequencies; Future; General Practitioners; Glaucoma; Goals; Grant; Health; Health Care Research; Health Services Research; Human; Institution; Interview; Knowledge; Laboratories; Lead; Leadership; Measures; Medical; Mentored Patient-Oriented Research Career Development Award; Mentors; Mentorship; Methods; Michigan; Modeling; Ophthalmologist; Ophthalmology; Optometrist; Outcome Measure; Patient Care; Patients; Periodicals; Persons; Primary Open Angle Glaucoma; Public Health Informatics; Recommendation; Research; Research Personnel; Residencies; Site; Specialist; Statistical Models; System; Technology; Testing; Time; Training; United States; United States National Aeronautics and Space Administration; Universities; Utah; Vision; Visual Fields; Workload; Writing; career; career development; clinical decision support; clinical decision-making; clinical encounter; clinical practice; cognitive task; design; effectiveness-implementation randomized trial; efficacy evaluation; efficacy testing; experience; field study; health care delivery; health information technology; implementation research; improved; indexing; individual patient; innovation; interoperability; iterative design; point of care; pre-clinical; preclinical efficacy; predictive modeling; pressure; prevent; professor; prototype; randomized trial; support tools; theories; usability

PROJECT SUMMARY/ABSTRACT Through the training outlined in this K23 award, Dr. Brian Stagg will become an independent investigator in health services research using health information technology to decrease glaucoma blindness by enhancing clinical decision making for glaucoma to ensure that patients receive appropriate glaucoma care. CANDIDATE BACKGROUND: Dr. Stagg is an Assistant Professor specialized in glaucoma at the University of Utah. Following ophthalmology residency, he completed a 2-year health services research fellowship at the University of Michigan and earned a Master of Health and Healthcare Research degree, followed by a glaucoma fellowship at Duke University. He has background experience in health services research, healthcare delivery research, data science, and biostatistics. CAREER DEVELOPMENT PLAN: To succeed as an independent investigator, Dr. Stagg needs additional training in: (1) Clinical Decision Support (CDS) system workflow and implementation research, (2) CDS system design and human factors research, (3) CDS system EHR integration using health informatics standards, and (4) research leadership and grant writing. The training and mentorship outlined in this K23 will give Dr. Stagg this needed expertise. MENTORS: Through the supportive research and mentorship environment at the University of Utah and his connections with mentors from the University of Michigan and Duke University, Dr. Stagg has put together an innovative interdisciplinary mentoring and advising team lead by Dr. Rachel Hess, his primary mentor. CLINICAL PROBLEM: Up to 30% of patients who are actively treated for glaucoma continue to have significant visual field loss and need intensification of treatment to lower eye pressure and prevent further loss. Proper identification and management of such progressive visual field loss is vital to prevent blindness from glaucoma. This is a challenge for clinicians caring for patients with glaucoma as they must incorporate large amounts of longitudinal data from many data sources accurately and efficiently. Optimized, workflow- appropriate CDS systems can help address this challenge. CDS systems present information to clinicians at the point of care to improve decision making. SPECIFIC AIMS: Dr. Stagg will (Aim 1) understand differences between ophthalmologic specialists and generalists in glaucoma clinical decision-making workflow and workload, (Aim 2) iteratively refine the Glaucoma CDS System and evaluate its efficacy in a pre-clinical setting, and (Aim 3) integrate the Glaucoma CDS System with the EHR and pilot for feasibility and usability in clinics to deliver personalized recommendations to clinicians for visual field testing frequency. The completion of these aims will result in (1) a rigorously developed, user-centered, scalable CDS system to help clinicians determine a personalized visual field testing frequency for patients with glaucoma and (2) generalizable knowledge that will support future CDS development for glaucoma and other eye conditions.

项目总结/摘要 通过在这个K23奖概述的培训，布赖恩斯塔格博士将成为一个独立的研究员， 卫生服务研究利用卫生信息技术，通过提高 青光眼的临床决策，以确保患者得到适当的青光眼护理。 候选人背景：Stagg博士是该大学青光眼专业的助理教授 来自犹他州。在眼科住院医师培训之后，他完成了为期2年的健康服务研究奖学金， 密歇根大学，并获得了健康和医疗保健研究硕士学位，其次是 杜克大学青光眼研究员。他在医疗服务研究、医疗保健和 交付研究、数据科学和生物统计学。职业发展目标：作为一名成功的 独立研究者，Stagg博士需要在以下方面接受额外培训：（1）临床决策支持（CDS）系统 工作流程及实现研究，（2）CDS系统设计及人因研究，（3）CDS系统 使用健康信息学标准的EHR集成，以及（4）研究领导和资助写作。的 本K23中概述的培训和指导将为Stagg博士提供所需的专业知识。导师：通过 犹他州大学的支持性研究和导师环境，以及他与 来自密歇根大学和杜克大学的导师，斯塔格博士已经把一个创新的 由他主要导师Rachel Hess博士领导的跨学科指导和咨询团队。临床 问题：高达30%的青光眼患者在积极治疗后， 视野损失，需要加强治疗以降低眼压并防止进一步损失。适当 识别和处理这种进行性视野丧失对于预防失明 青光眼这对于治疗青光眼患者的临床医生来说是一个挑战，因为他们必须将大量的 从多个数据源中准确、高效地获取大量纵向数据。优化的工作流程- 适当的CDS系统可以帮助应对这一挑战。CDS系统向临床医生提供信息， 护理点，以改善决策。具体目标：Dr. Stagg将（目标1）理解差异 青光眼临床决策工作流程中眼科专家和通才之间的关系， 工作量，（目标2）迭代地完善青光眼CDS系统，并在临床前评估中评价其疗效 目标3）将青光眼CDS系统与EHR整合，并进行可行性和可用性试验， 诊所向临床医生提供个性化的视野测试频率建议。完成 这些目标将导致（1）严格开发，以用户为中心，可扩展的CDS系统，以帮助临床医生 确定青光眼患者的个性化视野测试频率，以及（2）可推广的 这些知识将支持未来青光眼和其他眼部疾病的CDS开发。