Communicating Narrative Concerns Entered by RNs (CONCERN)

项目摘要/摘要 RNS(关注点)系统输入的传达叙事关注点是专家知识， 机器学习，预测模型(关注-PM)，产生早期预警分数(关注-EWS) 并作为临床决策支持(Concerns-CDS)实施，以提醒护士和医生 有失代偿风险的住院患者。关注-PM利用护理文档 模式作为护士决定增加监测和相关干预的代理衡量标准，这些模式包括 护士关心住院病人的指标--失代偿的关键早期指标。这五个人- 现场观察式实施研究是对我们成功的国家护理研究所的更新 研究(NINR)资助R01，在其中我们开发和评估了关注点(沟通 住院患者的预测模型和临床决策支持(CDS) 多点随机对照临床试验中的患者，中期结果为减少27%的可能性 临床医生接受关注CDS干预的患者与接受CDS干预的患者的住院死亡率 没有。关注-CDS提醒临床医生，患者面临风险的时间比领先的EWS1提前42小时。在这 更新R01，我们将进行五个站点的观察性实施研究，以评估公平性和 人口有效性的关注-PM，生态有效性的关注-CDS，并探讨 护理者生成的数据对关注者绩效的贡献-PM作为 我们的多站点护理数据科学和实施科学计划。EWS在健康领域得到了广泛的应用 然而，在全国范围内，我们发现缺乏证明外部有效性和 其他领先EWS的公平性2我们将利用5个不同的研究站点来测试公平性、总体有效性和 农村、郊区和城市环境的生态有效性。评估将由RE-AIM通知 (REACH、有效性、采用、执行和维护)和CFIR( 整合的框架 实施研究) 实施科学框架。本次R01续订的具体目标是： 目标1.将关注点-PM转换为2个额外的专科患者群体(急诊科和 住院儿科)，并添加健康的社会决定因素(SDOH)数据来评估模型 跨不同患者群体和卫生系统的校准和性能；目标2.评估 关注--在5个保健系统的所有成人住院病房、住院儿科病房实施CDS 在3个卫生系统和2个急诊科了解卫生系统和 与使用RE-AIM和CFIR成功实施相关的患者群体特征 框架和目标3.使用以患者为中心的设计方法，探索创建一个面向患者的 关注-PM和CDS对住院儿科患者照顾者的预测模型比较 性能，并向仅限临床医生的数据驱动模型提供额外的护理人员反馈。

PROJECT SUMMARY/ABSTRACT The Communicating Narrative Concerns Entered by RNs (CONCERN) system is an expert-knowledge, machine learning, predictive model (CONCERN-PM) that produces an early warning score (CONCERN-EWS) and is implemented as clinical decision support (CONCERN-CDS) to alert nurses and physicians about hospitalized patients who are at risk of decompensation. CONCERN-PM leverages nursing documentation patterns as a proxy measure of nurses’ decisions to increase surveillance and related interventions which are an indicator of nurse concern about hospitalized patients – a key early indicator of decompensation. This five- site observational implementation study is a renewal to our successful National Institute for Nursing Research (NINR) funded R01, in which we developed and evaluated the CONCERN (Communicating Narrative Concerns Entered by RNs) predictive model and clinical decision support (CDS) for hospitalized patients in a multi-site randomized controlled clinical trial, with interim results of a 27% reduced likelihood of inpatient mortality for patients whose clinicians received the CONCERN CDS intervention versus those who did not. CONCERN-CDS alerts clinicians that a patient is at risk 42 hours earlier than leading EWS1. In this renewal R01, we will conduct a five-site observational implementation study to evaluate fairness and population validity of the CONCERN-PM, ecological validity of the CONCERN-CDS, and explore the contribution of caregiver generated data to the performance of the CONCERN-PM as the next phase in our multi-site nursing data science and implementation science program. EWS are in broad use at health systems nationally, however, we have identified a lack of research findings demonstrating external validity and fairness in other leading EWS.2 We will leverage 5 diverse study sites to test fairness, population validity, and ecological validity across rural, suburban, and urban settings. The evaluation will be informed by the RE-AIM (Reach, Effectiveness, Adoption, Implementation and Maintenance) and CFIR ( Consolidated Framework for Implementation Research) implementation science frameworks. The specific aims of this R01 Renewal are to: Aim 1. Translate the CONCERN-PM to 2 additional specialty patient populations (emergency department and inpatient pediatrics) and with the addition of social determinants of health (SDOH) data to evaluate model calibration and performance across different patient populations and health systems; Aim 2. Evaluate CONCERN-CDS implementation across all adult inpatient units at 5 health systems, in inpatient pediatric units at 3 health systems and in the emergency department at 2 health systems to understand health system and patient population characteristics associated with a successful implementation using RE-AIM and CFIR Frameworks, and Aim 3. Using a patient-centered design approach, explore the creation of a patient-facing CONCERN-PM and CDS for caregivers of inpatient pediatric patients, to compare predictive model performance with additional caregiver feedback to the clinician-only data-driven model.