The VHA AMPREDICT Decision Support Tool: Translating Success to Point of Care

VHA AMPREDICT 决策支持工具：将成功转化为护理点

• 批准号: 10507769
• 负责人: Daniel C Norvell
• 金额: --
• 依托单位: VA PUGET SOUND HEALTHCARE SYSTEM
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10507769
• 关键词: Address; Affect; Amputation; Amputees; Award; Blood Vessels; Caring; Characteristics; Chronic; Climacteric; Clinical; Complex; Conflict (Psychology); Data; Decision Making; Development; Diabetes Mellitus; Diagnostic; Distal; Electronic Health Record; Ensure; Environment; Epidemiology; Equilibrium; Evaluation; Feedback; Foundations; Future; Gender; Goals; Grant; Health; Healthcare; Healthcare Systems; Home Page; Individual; Interview; Ischemia; Joints; Laboratories; Learning; Life; Limb structure; Literature; Lower Extremity; Manuals; Mental Health; Modeling; Operative Surgical Procedures; Outcome; Patients; Pattern; Perception; Peripheral arterial disease; Pharmaceutical Preparations; Physical Medicine; Physical Rehabilitation; Physicians; Podiatry; Population; Probability; Procedures; Process; Provider; Quality of life; Questionnaires; Race; Regrets; Rehabilitation therapy; Research; Resources; Risk; Sampling; Site; Social support; Structure; Surgeon; System; Testing; Therapeutic; Time; Training; Translating; Update; Veterans; Veterans Health Administration; Walking; Work; ankle joint; base; cancer diagnosis; care systems; clinical care; clinical decision support; clinical decision-making; clinical practice; comorbidity; data warehouse; demographics; design; effectiveness implementation study; efficacy evaluation; experience; healing; hospital readmission; implementation barriers; improved; individual patient; insight; military veteran; mortality; mortality risk; outcome prediction; point of care; predictive modeling; preservation; recruit; satisfaction; sex; shared decision making; success; support tools; tool; trend; usability; wound care

Amputation level decision making in patients with chronic limb threatening ischemia (CLTI) is challenging. The choice of amputation level in this population can profoundly affect risk of operative mortality, re-hospitalization, reamputation, functional mobility, and ultimately quality of life. One of the most important factors influencing the amputation level decision is the preservation of mobility because of its association with quality of life. However, the potential mobility benefits of more distal amputations may not be realized because of the increased risk of compromised healing, need for ongoing wound care, and ultimately reamputation to a higher level. An additional factor critical in decision making in this population is a mortality risk which is higher than the majority of cancer diagnoses. This limited survival creates an imperative for both surgeon and patient to make decisions that will best ensure the patient’s remaining life years conform to their values and priorities. Veteran Health Administration data suggest that between 2005-2014, the proportion of incident transmetatarsal (TM) amputations tripled from 10% to 30% of all CLTI amputations with a corresponding decrease in the proportion of transtibial (TT) and transfemoral (TF) amputations. The increase in TM amputations may be driven by the improvement in revascularizations, greater teamwork, and the assumption that preserving the ankle joint will enable superior mobility; however, it is unclear how the risks of not healing are considered in the decision. Balancing these risks is at the core of a complex shared decision-making (SDM) process between physicians and patients as they determine the “best” level of amputation. An important resource that enables successful implementation of SDM are clinical decision support tools (DSTs). They provide clinicians with patient specific risks for key outcomes in real time. To equip physicians with such a tool, we leveraged our prior prediction models to create the AMPREDICT DST. It is an online DST that includes a home page, predictor pages, and a result page with patient specific one-year mortality and reamputation risks and probability of achieving a basic level of independent mobility, at each of three amputation levels (TM TT, TF). It has undergone successful testing by VHA physicians nationwide. The successful implementation of the DST in clinical care requires buy in from user groups as well as the need to overcome potential implementation obstacles. Our evaluation of the DST in physician users has provided important insights that will be addressed in the current proposal. Many of the providers discussed the importance of DST integration into the EHR with auto-population of the predictors to minimize the implementation burden. Further, vascular surgeons recommended considering additional vascular diagnostic and therapeutic predictors that are viewed as important in the clinical decisional process, in the prediction models. This is supported by cutting edge developments in the recent literature. The goals of this grant are therefore threefold. First, we will enhance the quality of the AMPREDICT prediction models in a more contemporary population by replacing predictors not readily available in the EHR with similar predictors that are available, and the evaluation of additional vascular predictors. We will accomplish this through a systemic development process considering demographics, social support, comorbidities, health factors, prior vascular procedures, laboratory values, medications, and mental health predictors available in the EHR just prior to the amputation. Second, we will perform the necessary planning and programming to integrate the enhanced AMPREDICT DST into the VHA EHR to facilitate the auto-population through CPRS and Cerner. This will be accomplished through collaborating with the Amputee System of Care joint Cerner workgroup and collaborating with a firm with significant experience implementing risk calculators within the VHA EHR. Third, we will evaluate the usability and effect of the enhanced DST within the EHR on physician and patient decisional conflict, patient decisional regret and satisfaction. [Semi- structured qualitative interviews of surgeons will evaluate clinical/institutional factors that affect implementation.] Together this will result in an important clinical advancement in one of the most life changing clinical decisions.

慢性肢体威胁性缺血（CLTI）患者的截肢水平决策具有挑战性。这 在该人群中的截肢水平的选择可以深刻影响运营死亡率，重新院长， 反射，功能性流动性和最终的生活质量。影响的最重要因素之一 截肢级别的决定是由于其与生活质量的关联，因此保留了流动性。然而， 由于增加的风险增加 损害了治愈，需要持续的伤口护理，并最终获得更高水平的奖励。另一个 该人群决策至关重要的因素是高于大多数癌症的死亡风险 诊断。这种有限的生存使外科医生和患者都必须做出决定 最好确保患者剩余的终身年份符合他们的价值观和优先事项。资深卫生管理局 数据表明，在2005年至2014年之间，事件转质（TM）截肢的比例三倍 所有CLTI截肢的10％至30％，trantibial（TT）和 转际（TF）截肢。 TM截肢的增加可能是由改善的驱动 血运重建，更大的团队合作以及保留脚踝关节的假设将使优越 流动性；但是，目前尚不清楚如何在决定中考虑未治愈的风险。平衡这些风险 是医师和患者之间复杂共享决策（SDM）过程的核心 确定截肢的“最佳”水平。能够成功实施SDM的重要资源 是临床决策支持工具（DSTS）。他们为临床医生提供特定于患者的关键结果的风险 即时的。为了配备医生这样的工具，我们利用了先前的预测模型来创建 Ampredict DST。这是一个在线dst，包括主页，预测器页面以及患者的结果页面 特定的一年死亡率和成就风险以及实现基本独立水平的可能性 在三个截肢水平（TM TT，TF）中的每个迁移率。 VHA医生已经成功进行了测试 全国。 DST在临床护理中的成功实施也需要从用户组中购买 由于需要克服潜在的实施障碍。我们对物理用户中DST的评估 提供了当前提案中将解决的重要见解。许多提供商讨论了 DST集成到EHR中的重要性，并自动构建预测因子以最大程度地减少实施 负担。此外，血管外科医生建议考虑其他血管诊断和治疗 预测模型中，在临床决策过程中认为很重要的预测因子。这是 在最近的文献中得到了尖端发展的支持。因此，这笔赠款的目标是三倍。 首先，通过 用可用的类似预测指标替换EHR不容易获得的预测变量，并评估 其他血管预测因子。我们将通过系统的开发过程来实现这一目标 人口统计学，社会支持，合并症，健康因素，先前的血管程序，实验室价值观， 在截肢之前，EHR中可用的药物和心理健康预测因素。第二，我们会的 执行必要的计划和编程，以将增强的Ampredict DST集成到VHA中 EHR通过CPRS和CERNER促进自动人口。这将通过合作来实现 使用截肢者的护理系统联合Cerner工作组，并与具有丰富经验的公司合作 在VHA EHR中实施风险计算器。第三，我们将评估增强的可用性和效果 DST在EHR内进行身体和患者决策冲突，患者决策性的遗憾和满意度。 [半- 外科医生的结构性定性访谈将评估影响实施的临床/机构因素。] 这将共同导致在最终改变生活的临床决策之一中的重要临床进步。