Developing Interoperable tools for anxiety and depression screening

开发用于焦虑和抑郁筛查的可互操作工具

• 批准号: 10512151
• 负责人: Heidi Munger Clary
• 金额: $ 7.75万
• 依托单位: WAKE FOREST UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10512151
• 关键词: Anxiety; Applications Grants; Caring; Chronic; Clinic; Clinic Visits; Clinical; Collection; Custom; Data; Data Collection; Databases; Depression screen; Discipline of Nursing; Effectiveness; Electronic Health Record; Electronic Mail; Eligibility Determination; Epilepsy; Evidence based intervention; Future; Health; High Prevalence; Individual; Intervention Trial; Investigation; Link; Manuals; Measures; Medical; Mental Depression; Methods; Modality; Modeling; Monitor; Multicenter Studies; Neurologist; Neurology; Nursing Staff; Outcome; Outcome Measure; Patient Outcomes Assessments; Patients; Persons; Primary Health Care; Principal Investigator; Process; Process Measure; Provider; Psychiatry; Quality of life; Questionnaires; Randomized; Reporting; Reproducibility; Research; Site; Surveys; Symptoms; System; Systems Integration; Testing; Text; Text Messaging; Time; Translations; Treatment outcome; Visit; Work; anxiety symptoms; anxiety treatment; application programming interface; arm; base; clinical implementation; collaborative care; comorbidity; depressive symptoms; discrete data; effectiveness implementation trial; effectiveness study; electronic data; evidence base; implementation research; implementation strategy; implementation study; implementation trial; instrument; interoperability; medical specialties; nervous system disorder; patient health information; patient portal; patient screening; primary outcome; programs; recruit; screening; systems research; theories; tool; uptake

Project Summary Anxiety and depression are prevalent in neurological disorders and other chronic conditions requiring specialty care, and these comorbidities are often under-recognized and undertreated, despite greater impact on outcomes than the primary chronic condition. Clinician time-related barriers to screening contribute to undertreatment. Epilepsy is a key example, with well-documented undertreatment of anxiety and depression despite high prevalence and impact, and data indicating that patients prioritize treatment and prefer to be treated in a neurology clinic for depression and anxiety. Tools and strategies are needed to reduce burden of anxiety and depression screening in neurology clinics and other subspecialty settings, to close care gaps and facilitate multicenter implementation and effectiveness studies of evidence-based interventions such as collaborative care models that involve repeated symptom monitoring with anxiety and depression instruments. Our group successfully implemented screening in a tertiary epilepsy center using electronic health record (EHR)-based tools enabling patient self-completion of instruments after brief nursing staff activation. This more than quadrupled screening, but a substantial gap remained due to the nursing activation step, and barriers to scaling included lack of EHR/research database integration and need for custom EHR build at each potential site for future multicenter studies. Interoperable tools facilitating independent patient self-completion are needed to support multicenter intervention trials with symptom monitoring and scale implementation strategies. Thus, in this proposal we aim to develop and refine interoperable tools for anxiety and depression screening. Specifically, in Aim 1 we will evaluate screening completion (primary) and process measures comparing interoperable, REDCap-based methods to EHR patient portal-based methods for delivering validated anxiety and depression instruments to epilepsy patients. This will be accomplished in a randomized study with N=220 individuals per arm comparing 4 delivery modalties (Twilio text vs. REDCap survey vs. EHR portal questionnaires with reminder vs. standard EHR portal questionnaires). In Aim 2, we will evaluate and implement a reproducible approach to EHR and research system integration of Epic EHR flowsheet data with REDCap via Kit Flowsheets Application Programming Interface (API). We will also develop and disseminate a governance process to accomplish bidirectional integration for EHR flowsheet data with REDCap via Epic’s AddFlowsheetValue API. This R03 project will be instrumental to support next-step larger scale grant applications for the principal investigator examining collaborative care model effectiveness in neurology settings and screening implementation. The proposal is relevant across chronic conditions treated by subspecialists and highly translational, overcoming key roadblocks to translation in clinical implementation research involving the EHR.

项目摘要 焦虑和抑郁在神经系统疾病和其他慢性疾病中普遍存在， 专科护理，这些合并症往往认识不足和治疗不足，尽管更大的影响， 比原发性慢性病更重要。临床医生与时间相关的筛选障碍有助于 治疗不足癫痫是一个重要的例子，有充分的证据表明， 尽管患病率和影响很高，但数据表明患者优先考虑治疗， 因抑郁和焦虑在神经科诊所接受治疗需要有工具和战略来减轻 在神经科诊所和其他专科环境中进行焦虑和抑郁筛查，以缩小护理差距， 促进循证干预措施的多中心实施和有效性研究， 协作护理模式，包括使用焦虑和抑郁工具进行反复症状监测。 本研究小组成功地在一个三级癫痫中心使用电子健康记录进行了筛查 （EHR）为基础的工具，使病人自我完成的文书后，简短的护理人员激活。这种更 比四倍的筛选，但由于护理激活步骤和障碍， 扩展包括缺乏EHR/研究数据库集成，以及需要在每个潜力上定制EHR构建 未来多中心研究的网站。促进独立患者自我完成的互操作工具包括 需要通过症状监测和量表实施策略支持多中心干预试验。 因此，在这项提案中，我们的目标是开发和完善焦虑和抑郁筛查的互操作工具。 具体而言，在目标1中，我们将评估筛选完成（主要）和过程措施， 可互操作的、基于REDCap的方法到基于EHR患者门户的方法，以提供经验证的焦虑 和抑郁仪器给癫痫病人。这将在一项随机研究中完成，N=220 比较4种交付模式（Twilio文本与REDCap调查与EHR门户网站） 带提醒的问卷与标准EHR门户问卷）。在目标2中，我们将评估和 实现EHR和研究系统集成Epic EHR流程图数据可再现方法， 通过套件流程图应用程序编程接口（API）实现REDCap。此外，我们亦会制订及派发 通过Epic的REDCap实现EHR流程图数据与REDCap的双向集成 AddFlowsheetValue API。 这个R 03项目将有助于支持下一步更大规模的赠款申请， 主要研究者检查协作护理模式在神经病学设置和筛查中的有效性 实施.该提案与由亚专家治疗的慢性疾病相关， 翻译，克服关键的障碍，翻译临床实施研究涉及电子病历。