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.

项目总结