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

项目摘要/摘要 我们的长期目标是确保临床决策支持(CDS)针对多学科中的护士 纵向护理计划为循证护理决策提供高效和有效的支持 改善患者的预后。有证据表明，住院临终关怀(EoL)之间存在巨大差距 患者对舒适和尊严死亡的渴望以及他们所得到的护理。护士，他们提供了大部分 对于住院患者的实际护理，往往准备不足，无法提供以患者为中心的EoL护理。有耐心的 在正确的时间以正确的格式在护理点向护士提供的具体证据具有 极大地改善患者预后的潜力。在我们团队的基础研究中，我们迭代地构建 交互式CDS原型并演示了临床前(基于模拟)随机化的可行性 使用功能交互式CDS原型(文本、文本+表格；文本+图形、对照)的对照试验(RCT)，60 比较不同组别护士对患者预后的影响。调查结果显示， 所有三种CDS格式的护理决策计划都与EoL患者的预后改善有关。我们也 发现在不同的CDS格式下，护士的决策时间随护士的图形素养(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。这些发现有 CDS干预措施转化为临床护理的重要意义。确认的关键一步 这些发现是充分检验GL与CDS格式之间关系的充分动力 临床(基于模拟)随机对照试验，样本为具有全国代表性的220名注册护士。这个 测试策略具有创新性和重要意义，因为它允许将结果推广到 遵守国家术语和护理计划标准，避免发生意外后果 当构思不周的CDS过早地被实施到实时电子健康记录系统(EHR)中时。我们 现在提出以下建议：目标1.比较四个CDS组(文本、文本+表格、文本+图表、定制的 对CDS决策时间和患者预后的影响。我们假设定制的CDS小组将拥有 比其他CDS组更快的决策时间(主要)和更好的患者结果(次要)。目标2. 检查其他护士特征(例如计算能力、格式偏好、人口统计数据)之间的关联 [教育，经验])以CDS格式显示CDS决策时间和患者结果。我们假设 (A)在文本+表格下，较高的计算能力与更快的决策时间和更好的患者结局相关 文本+图表，(B)分配的格式和护士偏好之间的一致性与更快的决策相关 时间和更好的患者结果。研究结果将使基于更精细模型的CDS定制得到改进 在不同的CDS格式下预测RN的决定时间和患者结局。

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.