Personalizing Clinical Decision Support for Heart Failure Treatment to Clinicians' Needs

根据临床医生的需求个性化心力衰竭治疗的临床决策支持

• 批准号: 10524894
• 负责人: Katy E Trinkley
• 金额: $ 16.52万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10524894
• 关键词: Address; Adoption; Adrenergic beta-Antagonists; Architecture; Asthma; Attention; Blood Pressure; Cardiology; Caring; Categories; Clinic; Clinical; Data; Development; EFRAC; Effectiveness; Ensure; Evaluation; Fatigue; Future; Glucose; Goals; Guidelines; Health system; Heart failure; Informatics; Interview; Lead; Mentors; Methods; Mineralocorticoid Receptor; Mission; National Heart, Lung, and Blood Institute; Outcome; Patient Care; Patient-Focused Outcomes; Patients; Pattern; Positioning Attribute; Practical Robust Implementation and Sustainability Model; Primary Health Care; Public Health; Quality of life; Randomized; Randomized Controlled Trials; Reach Effectiveness Adoption Implementation and Maintenance; Regulation; Research; Research Personnel; Resources; Scientist; Sodium; System; Testing; Time; Training; Translations; Treatment Failure; Work; Workload; antagonist; base; behavioral economics; care outcomes; clinical decision support; computerized; contextual factors; design; experience; high risk; implementation framework; implementation outcomes; implementation science; improved; inhibitor; innovation; iterative design; operation; patient population; personalized decision; pragmatic trial; preference; programs; prototype; randomized trial; success; support tools; therapy outcome; trial design; usability; valsartan

PROJECT SUMMARY Clinical decision support (CDS) tools are pervasive and can “nudge” clinicians to make the best decisions easy, yet currently lead to minimal improvements in patient outcomes. Although often ignored, consideration of contextual factors and minimizing irrelevant information improves CDS outcomes. To minimize irrelevance, currently existing, ‘traditional CDS’ are often designed to be patient-specific, but are not tailored to clinicians. For example, traditional CDS address common prescribing misconceptions that are not relevant for all clinicians. However, prescribing patterns could be used to determine whether prescribing misconceptions might exist and then conditionally present information within a ‘personalized CDS’ to address a specific clinician’s misconceptions; thereby minimizing irrelevance and alert fatigue. A ‘personalized CDS’ could substantially improve guideline-directed management and therapy (GDMT) for the many suboptimally treated patients with heart failure and reduced ejection fraction (HFrEF). Aim 1: Design and build prototypes of traditional and personalized CDS to address common misconceptions of GDMT for HFrEF. We will create a personalized and traditional CDS prototype for 4 categories of GDMT: beta blockers, sacubitril/valsartan, mineralocorticoid receptor antagonists and sodium/glucose cotransport 2 inhibitors. Clinicians will prioritize the misconceptions to address. The traditional CDS will address all prioritized misconceptions, while the personalized CDS will conditionally address the misconceptions based on clinician-specific prescribing patterns. To account for contextual factors, we will use the Practical Robust Implementation and Sustainability Model (PRISM) to guide design and usability testing. Aim 2: Pilot the traditional and personalized CDS tools in real-world care settings. Aim 3: Compare the traditional and personalized CDS in a pragmatic randomized controlled trial. Cardiology and primary care clinics at one health system will be cluster-randomized. We will use sequential mixed methods and PRISM evaluation metrics to compare the two CDS tools. Quantitative outcomes include reach, adoption and effectiveness of prescribing. We will interview 15 frontline clinicians and 5 leaders to 1) identify PRISM factors influencing implementation outcomes, and 2) plan for external dissemination. This proposal was designed to address my training gaps: 1) EHR architecture, 2) behavioral economics/nudges, and 3) pragmatic trial design. Completion of this proposal will ensure my development into an independent investigator that leverages implementation science to create innovative CDS solutions that consistently and effectively optimize GDMT for HFrEF across health systems. This research is significant because it has the potential to substantially improve GDMT and outcomes for high-risk patients with HFrEF. Our innovative, personalized CDS challenges the status quo of “one size fits all” CDS by individualizing CDS to both patients and clinicians; a paradigm-shift that will have far-reaching influence on CDS development and GDMT.

项目摘要 临床决策支持（CDS）工具无处不在，可以“轻推”临床医生做出最好的决定容易， 但目前导致患者结果的最小改善。虽然经常被忽视，但考虑到 背景因素和最小化不相关信息改善了CDS结果。为了尽量减少无关性， 目前存在的“传统CDS”通常被设计为患者特异性的，但不是为临床医生定制的。为 例如，传统的CDS解决了与所有临床医生不相关的常见处方误解。 然而，处方模式可用于确定是否可能存在处方误解， 然后在“个性化CDS”内有条件地呈现信息， 误解;从而最大限度地减少无关性和警觉疲劳。“个性化CDS”可能会大大提高 改善指南指导的管理和治疗（GDMT）的许多次优治疗的患者， 心力衰竭和射血分数降低（HFrEF）。 目标1：设计和构建传统和个性化CDS的原型，以解决常见的 GDMT对HFrEF的误解。我们将创建一个个性化的和传统的CDS原型为4 GDMT的类别：β受体阻滞剂、沙库巴曲/缬沙坦、盐皮质激素受体拮抗剂和 钠/葡萄糖共转运蛋白2抑制剂。临床医生将优先考虑要解决的误解。传统 CDS将解决所有优先的误解，而个性化的CDS将有条件地解决 基于临床医生特定处方模式的误解。为了说明上下文因素，我们将使用 实用稳健实施和可持续性模型（PRISM），以指导设计和可用性测试。 目标2：在现实世界的护理环境中试用传统和个性化的CDS工具。 目的3：在一项实用的随机对照试验中比较传统和个性化CDS。 一个卫生系统的心脏病科和初级保健诊所将被随机分组。我们将使用顺序 混合方法和PRISM评价指标来比较两种CDS工具。定量结果包括 处方的范围、采用和有效性。我们将采访15名一线临床医生和5名领导，以1） 确定影响实施结果的PRISM因素，2）计划对外传播。 这个建议旨在解决我的培训差距：1）EHR架构，2）行为经济学/轻推， 3）务实的试验设计。完成这份提案将确保我发展成为一个独立的 研究人员利用实施科学来创建创新的CDS解决方案， 有效优化卫生系统中HFrEF的GDMT。这项研究意义重大，因为它具有 有可能显著改善HFrEF高危患者的GDMT和结局。我们的创新， 个性化CDS通过对两种患者的个性化CDS挑战了“一刀切”CDS的现状 和临床医生;一个范式的转变，将有深远的影响CDS的发展和GDMT。