Adaptation and pilot implementation of a validated, electronic real time clinical decision support tool for care of Pneumonia patients in 12 Utah Urgent Care Centers

项目摘要 通过良好的医疗服务，提高临床医生准确诊断肺炎和选择适当治疗的能力 设计了临床决策支持(CDS)，从而提高了患者的安全性。肺炎CDS从历史上看 一直专注于住院设置，但门诊护理设置具有高肺炎患者量和 不同的护理流程也需要CDS。我们建议调整和评估一种创新的、经过验证的电子产品 基于肺炎(EPNa)到紧急护理共识指南的临床决策支持(CDS)工具 中心(UCC)。该方案支持四个目标：1)使ePNa适应UCC及之后的硅胶测试，并进行试点 在UCC换班期间的“超级用户”临床医生之间，并评估其可用性。EPNa需要为有限的人做出调整 患者数据可在UCC中获得，校准严重程度测量以降低观察到的死亡率，以及胸部 影像提示肺炎患者的体征和症状。UCC的EPNa将纳入人工 智能CheXpert模型，可提供实时(数秒内)电子分类胸部图像 肺炎的诊断和治疗要素(放射学肺炎、单叶与多叶、胸膜 渗出)。2)使用CFIR框架、UCC临床医生的焦点小组和工作流程观察来确定 使ePNa适应和实施《公约》的障碍和促进者。3)测试实施策略 通过在两个随机选择的山间医疗UCC集群中的一个部署ePNa，每个集群大约 每年800名肺炎患者--另一组为常规护理对照组。4)共同原发结果是a)患者 在没有胸部影像的情况下被诊断为肺炎，在ePnA组中≥将降低50%。B)抗生素 治疗肺炎的处方将是≥90%与共识指南一致，并在 EPNa簇。安全措施将是计划外的后续7天急诊室就诊/住院和30天 死亡率。基于这项严格的先导性研究，我们预计随后将进行一项多系统集群随机试验 包括犹他州以外的Cerner系统。 我们的工作结合了CDS的五项权利，以确保该技术的优势在 临床环境。我们将利用创新肺炎研究、开创性CDS和 为了成功地完成这项提议，InterMountain提供了实施科学。该提案将是 通过与PCORnet学习健康网的山间关系促进和传播 系统网络、PCOR CDS学习网络、医疗保健服务平台联盟、Cerner和 临床试验.gov。 我们的创新提案承诺提高未被研究的肺炎疑似患者的安全性， 大容量非卧床护理环境。

Project Summary Clinicians’ ability to accurately diagnose pneumonia and choose appropriate treatment is enhanced by well- designed clinical decision support (CDS), thereby increasing patient safety. Pneumonia CDS has historically been focused on inpatient settings, but ambulatory care settings with high pneumonia patient volumes and different care processes also need CDS. We propose to adapt and evaluate an innovative, validated electronic clinical decision support (CDS) tool based on consensus guidelines for pneumonia (ePNa) to urgent care centers (UCC). The proposal supports four aims: 1) Adapt ePNa for UCC and after in silico testing, pilot it among “super user” clinicians during UCC shifts and assess its usability. ePNa needs adaptation for the limited patient data available in UCC, calibration of severity measures for lower observed mortality, and a chest imaging prompt in patients with pneumonia signs and symptoms. ePNa for UCC will incorporate the artificial intelligence CheXpert model to provide real-time (within seconds) electronic classification of chest images for elements of pneumonia diagnosis and treatment (radiographic pneumonia, single vs multiple lobes, and pleural effusion). 2) Use the CFIR framework, a focus group of UCC clinicians, and workflow observations to identify barriers and facilitators to adaptation and implementation of ePNa to UCC. 3) Test the implementation strategy by deploying ePNa at one of two randomly chosen Intermountain Healthcare UCC clusters each with about 800 annual pneumonia patients - the other a usual care control. 4) Co-primary outcomes are a) Patients diagnosed with pneumonia without chest imaging will be ≥50% lower in the ePNa cluster. b) Antibiotic prescribing for treatment of pneumonia will be ≥90% consistent with consensus guidelines and higher in the ePNa cluster. Safety measures will be unplanned subsequent 7-day ED visits/hospitalizations and 30-day mortality. Based on this rigorous pilot study, we anticipate a subsequent multi-system cluster-randomized trial including Cerner systems outside Utah. Our work incorporates the Five Rights of CDS to ensure that the strengths of this technology are optimized in the clinical environment. We will leverage experience in innovative pneumonia research, pioneering CDS, and implementation science available at Intermountain to successfully complete this proposal. The proposal will be facilitated by and disseminated through Intermountain relationships with the PCORnet Learning Health Systems Network, PCOR CDS Learning Network, the Healthcare Services Platform Consortium, Cerner, and clinicaltrials.gov. Our innovative proposal promises to advance safety for patients suspected of pneumonia in an understudied, high-volume ambulatory care setting.