Tailored Clinical Decision Support Formats Designed to Improve Palliative Care for Cancer and Chronically Ill Patients: A Pre-Clinical Test

项目总结/摘要 我们的长期目标是确保针对多学科护士的临床决策支持（CDS） 纵向护理计划为基于证据的护理决策提供了高效和有效的支持， 改善患者预后。有证据表明，住院治疗的生命末期（EoL） 病人对舒适和有尊严的死亡的渴望以及他们所得到的照顾。护士，他们提供了大多数 为住院患者提供的实际护理，通常准备不足，无法提供以患者为中心的EoL护理。患者 在正确的时间和以正确的格式在护理点交付给护士的具体证据具有 极大地改善患者预后的潜力。在我们团队的基础研究中，我们反复构建了 交互式CDS原型，并证明了临床前（基于模拟）随机 使用功能交互式CDS原型（文本，文本+表格;文本+图表，对照）的对照试验（RCT），60 护士比较各组对患者结局的影响。研究结果显示， 与改善EoL患者结局相关的护理计划决策的所有三种CDS格式。我们也 发现在不同的CDS格式下，护士的决策时间随着护士的图形素养（GL）而变化， 这表明护士的最佳CDS格式可能取决于他们的GL水平。这些发现 将CDS干预转化为临床护理的重要意义。这是确认 这些发现是为了充分测试GL和最佳CDS格式之间的关系， 临床（基于模拟）RCT，全国代表性样本为220名注册护士受试者。的 测试策略是创新的和重要的，因为它允许将发现推广到系统， 遵守国家术语和护理计划标准，避免发生意外后果 当构思拙劣的CDS过早地被实施到实时电子健康记录系统（EHR）中时。我们 现提出以下建议：目标1。比较四个CDS组（文本、文本+表格、文本+图表、定制）， 对CDS决策时间和患者结局的影响。我们假设定制CDS组将具有 与其他CDS组相比，决策时间更快（主要）和患者结局更好（次要）。目标二。 检查其他护士特征的关联（例如，计算能力，格式偏好，人口统计学 [教育，经验]）与CDS决策时间和CDS格式的患者结局。我们假设 (a)较高的计算能力与更快的决策时间和文本+表格下更好的患者结局相关， 文本+图形，（B）指定格式和护士偏好之间对齐与更快的决策相关 时间和更好的患者结果。调查结果将使改进的CDS剪裁的基础上更精细的模型 预测RN在不同CDS格式下的决策时间和患者结果。

Project Summary/Abstract Our long-term goal is to ensure that clinical decision support (CDS) targeting nurses within the multidisciplinary longitudinal care plan provides efficient and effective support for evidence based nursing care decisions that improve patient outcomes. Evidence points to a tremendous gap between hospitalized end-of-life (EoL) patients' desire for comfort and dignified death and the care they receive. Nurses, who provide the majority of hands-on care for hospitalized patients, are often ill-prepared to provide patient-centered EoL care. Patient specific evidence delivered at the point-of-care to nurses at the right time and in the right format has the potential to dramatically improve patient outcomes. In our team's foundational research, we iteratively built interactive CDS prototypes and demonstrated the feasibility of a pre-clinical (simulation based) randomized controlled trial (RCT) with functional interactive CDS prototypes (text, text+table; text+graph, control) with 60 nurses to compare groups for effects on patient outcomes. The findings showed significant positive impact of all three CDS formats on plan of care decisions associated with improved outcomes for EoL patients. We also found that the nurse's decision time varied with the nurse's graph literacy (GL) under different CDS formats, indicating that the optimal CDS format for a nurse might depend on their GL level. These findings have important implications for translation of CDS interventions into clinical care. A crucial step toward confirming these findings is to fully test the relationship between GL and optimal CDS format in an adequately powered clinical (simulation based) RCT with a nationally representative sample of 220 registered nurse subjects. The testing strategy is innovative and significant since it allows the generalization of findings to systems that comply with national terminology and care plan standards and avoids the unintended consequences that occur when ill-conceived CDS is implemented into live electronic health record systems (EHRs) prematurely. We now propose the following: Aim 1. Compare the four CDS groups (text, text+tables, text+graphs, tailored) for effects on CDS decision time and patient outcomes. We hypothesize that the tailored CDS group will have faster decision time (primary) and better patient outcomes (secondary) than the other CDS groups. Aim 2. Examine associations of other nurse characteristics (e.g., numeracy, format preference, demographics [education, experience]) with CDS decision time and patient outcomes by CDS formats. We hypothesize that (a) higher numeracy is associated with faster decision time and a better patient outcome under text+table and text+graph, (b) alignment between assigned format and nurse preference is associated with faster decision time and better patient outcomes. Findings will enable improved CDS tailoring based on more refined models that predict the RN's decision time and patient outcome under different CDS formats.