Describing, Contrasting, and Visualizing End-of-Life Care in the 21st Century

描述(由申请人提供)：我们的长期目标是揭示支持患者尊严和舒适的临终护理(EOL)护理的基准和最佳实践。每年花费数百万美元用于对濒临死亡的住院患者进行价值可疑的治疗。随着电子健康记录(EHR)和标准化术语的成熟，现在可以获取数据并使用它来确定有效护理或不良事件风险的基准和最佳做法。在我们对包含39,322个护理事件的实际护理实践的广泛手部数据库的初步研究中，我们确定了1,394名EOL患者，并检查了他们的“疼痛护理”，以证明我们方法的可行性和确定有效疼痛基准的能力。这项研究得出了4项具有统计学意义和临床重要性的基准：(1)51%的EOL患者在出院至临终关怀或死亡时未能达到预期的疼痛结果；(2)在护理的前24小时内实现的疼痛控制可以预测整个住院期间的疼痛控制；(3)同时进行心肺和疼痛诊断的EOL患者的疼痛结果显著低于那些没有诊断为EOL的患者；以及(4)某些干预措施更有可能实现疼痛控制。我们将这些Pain基准转换为EHR用户界面，现在可以通过一个预期的样本进行可用性测试。在这些重要发现的基础上，我们建议为住院的EOL患者常见的5个额外护理问题和5个问题组合确定基准和最佳实践。从4家中西部医院8个不同急诊病房的1,394名EOL患者的护理计划历史的验证数据集，我们将使用以下属性来描述EOL护理：1)患者和提供者的人口统计学；以及2)护理诊断、干预和结果，因为它们在每个患者的护理过程中演变。一旦我们确定了基准，然后我们将建立一个基准系统，在EHR计算机屏幕上以可视化的方式呈现结果，帮助护士在计划和记录EHR中的护理时查看和使用基准。我们的具体目标是：Aim1。在手中记录的所有属性中确定模式，以便在揭示基准和最佳实践的属性之间建立有意义的关联。目的2.在75名护士的不同样本中，确定新的可视化屏幕的可用性(可访问性、视觉吸引力、内容效用以指导护理点的预期使用)，这些屏幕显示结果模式评级的基准(在个人、单位、医院和4家医院之间)和最佳实践。研究结果将为未来基于实践的前瞻性研究提供信息，以验证基准系统的有效性，从而为住院的EOL患者产生预期的结果。迫切需要这样的发现，以实现最佳实践护理，以支持住院的EOL患者在死亡时的尊严和舒适度。

DESCRIPTION (provided by applicant): Our long-term goal is to reveal benchmarks and best practices for end-of-life (EOL) nursing care that support patients' dignity and comfort. Millions of dollars are spent each year on treatments of questionable value to hospitalized patients who are near death. The maturation of the electronic health records (EHRs) and standardized terminologies now make it possible to capture data and use it to determine the benchmarks and best practices of effective care or risks for adverse events. In our preliminary study of an extensive HANDS database of actual nursing care practices with 39,322 care episodes, we identified 1,394 EOL patients and we examined their "pain care" to demonstrate the feasibility of our methods and adequacy of power to determine effective pain benchmarks. This study yielded 4 statistically significant and clinically important benchmarks: (1) 51% of EOL patients failed to meet expected pain outcomes at discharge to hospice or death; (2) pain control achieved in the first 24 hours of care was predictive of pain control for the entire stay; (3) EOL patients with both cardiopulmonary and pain diagnoses had significantly poorer pain outcomes than those who do not; and (4) certain interventions were more likely to achieve pain control. We translated these pain benchmarks into an EHR user interface that is now ready for usability testing by a prospective sample. Building on these important findings, we propose to identify benchmarks and best practices for 5 additional care problems and 5 combinations of problems that are common to hospitalized EOL patients. From the validated dataset of care plan histories for 1,394 EOL patients from 8 different acute care units in 4 Midwestern hospitals, we will characterize EOL care using the following attributes: 1) patient and provider demographics; and 2) the nursing diagnoses, interventions, and outcomes as they evolved during each patient's care episode. Once we determine the benchmarks, then we will build a benchmarking system that presents the findings visually on EHR computer screens that help nurses to see and use the benchmarks as they plan and document care in the EHR. Our specific aims are to: Aim1. Determine patterns among all attributes recorded in HANDS for meaningful associations among the attributes that reveal benchmarks and best practices. Aim 2. In a diverse sample of 75 nurses, determine the usability (accessibility, visual appeal, content utility to guide intended use at the point of care) of new visualization screens that display the benchmarks for outcome pattern ratings (at the level of the person, unit, hospital, and across the 4 hospitals) and best practices. Study findings will inform future prospective practice-based research to verify the effectiveness of the benchmarking system to produce desired outcomes for hospitalized EOL patients. Such findings are urgently needed to enable best practice nursing care that supports hospitalized EOL patients' dignity and comfort as they die.