Clinical decision support optimizing NEC prevention implementation in NICU

描述（由申请人提供）：在使用临床决策支持的新生儿重症监护中，本职业发展建议的重点是改善早产儿坏死性小肠结肠炎（NEC）预防和早期识别的循证实践应用。NEC是一种威胁脆弱早产儿生命的灾难性并发症，然而采用预防和早期识别措施（例如优先使用人乳；采用标准化喂养方案；输血和抗生素管理）的差异很大，NEC的发病率也存在很大差异。父母在NEC预防中发挥着关键作用（例如提供母乳），但迄今为止，作为合作伙伴的参与还不够。NEC占美国新生儿重症监护病房费用的20%，在医院产后发展较晚，可能突然发作，但直到现在，还没有指导早期NEC识别的工具。为了满足这一需求，我们的团队导出并验证了一个称为GutCheckNEC的NEC风险决策规则，以准确区分NEC。使用临床决策支持（CDS）将预防实践整合到临床工作流程中已被证明可以提高对推荐护理的依从性。然而，新生儿重症监护病房中CDS的使用和评估都很稀少，而且据我们所知，尚无与CDS支持预防NEC相关的研究。通过将研究转化为实践（TRIP）框架用于实施科学，在两个nicu中使用中断时间序列设计，我们将NEC- zero集成到CDS中，以适应临床医生的工作流程，优化可用性，并测试对NEC疾病，新生儿营养和父母满意度的影响。中心假设是，当使用CDS时，对指南推荐的NEC预防和早期识别实践（称为“NEC- zero”，并使用依从性评分进行评估）的依从性将得到改善，NEC疾病将下降。首先，临床医生的工作流程将通过与当地临床医生的访谈构建的工作流程图来描述，NEC-Zero以标准订单集、警报、提醒和趋势数据的形式集成到CDS中（目标1）。然后，使用模拟的NEC场景和迭代评估，NEC- zero可用性将得到优化（目标2）。最后，通过对NEC- zero实施前后1年的指标进行中断时间序列分析，我们将比较NEC疾病、新生儿营养和父母满意度结果的趋势；然后描述NEC- 0后临床医生CDS结局（依从性评分、使用反应率、满意度、CDS意外后果的感知）与NEC疾病结局之间的关系（目标3）。在Daniel Malone博士（注册会计师）和Robert Greenes博士（医学博士）的指导下，对可用的临床决策支持进行正式培训，以补充实施科学的理论和方法培训。玛丽塔·蒂特勒和梅勒妮·贝尔。随着时间的推移，我们将能够将CDS的自动化和测试应用于新生儿重症监护病房的其他临床挑战，以实现本研究项目的目标，即降低新生儿并发症的发病率和死亡率，并限制成本。

DESCRIPTION (provided by applicant): In neonatal intensive care using clinical decision support, the focus of this career development proposal is to improve application of evidence-based practices for prevention and early recognition of necrotizing enterocolitis (NEC) among premature infants. NEC is a catastrophic complication threatening the life of fragile premature infants, yet adoption of prevention and early recognition practices (e.g. preferential use of human milk; adoption of standardized feeding protocols; transfusion and antibiotics management) differ widely as do NEC rates. Parents play a key role in NEC prevention (e.g. providing mother's own milk), but heretofore, have been insufficiently engaged as partners. Accounting for 20% of US NICU costs, NEC develops late in the hospital postnatal course and can strike suddenly but until now, no tools to guide early NEC recognition were available. To address this need, a NEC risk decision rule, called GutCheckNEC was derived and validated by our team to accurately discriminate NEC. Integration of prevention practices into clinical workflow using clinical decision support (CDS) has been shown to improve adherence to recommended care across settings. Yet, both the use and evaluation of CDS in NICUs are sparse, and we know of no studies related to CDS support for prevention of NEC. Informed by the Translating Research Into Practice (TRIP) framework for implementation science, in two NICUs using an interrupted time series design, we will integrate NEC-Zero into CDS to fit clinician workflow, optimize usability, and test effects on NEC disease, neonate nutrition and parental satisfaction. The central hypothesis is that adherence to guideline-recommended NEC prevention and early recognition practices (called "NEC-Zero" and evaluated using an adherence score) will improve when delivered using CDS and NEC disease will decline. First, clinician workflow will be described using workflow maps constructed from interviews with local clinicians and the NEC-Zero integrated into CDS in the form of standard order sets, alerts, reminders and trend data (Aim 1). Then, using a simulated NEC scenario and iterative evaluation, NEC-Zero usability will be optimized (Aim 2). Finally, with an interrupted time series analysis from indicators in the 1 year prior to and 1 year after NEC-Zero implementation, we will compare the trend for NEC disease, neonate nutrition, and parent satisfaction outcomes; then describe the relationship between post-NEC-Zero clinician CDS outcomes (adherence scores, use response rates, satisfaction, perception of unintended consequences of CDS) and NEC disease outcomes (Aim 3). Formal training in usable clinical decision support under the mentorship of Daniel Malone, PhD, RPh & co-mentor Robert Greenes, MD, PhD will complement training in theories and methodologies of Implementation Science mentored by Drs. Marita Titler and Melanie Bell. Over time we will be able to apply the automation and testing of CDS for multi-faceted interventions to other clinical challenges in NICUs to achieve the goal for this program of research, which is to reduce morbidity and mortality from neonatal complications and limit costs.