Clinical decision support optimizing NEC prevention implementation in NICU

临床决策支持优化 NEC 预防在 NICU 的实施

• 批准号: 8923171
• 负责人: Sheila Maria Gephart
• 金额: $ 13.71万
• 依托单位: UNIVERSITY OF ARIZONA
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-30 至 2019-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8923171
• 关键词: Clinical; decision; support; optimizing; NEC

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.

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，该职业发展提案的重点是改进基于证据的实践的应用，以预防和早期识别早产儿坏死性小肠结肠炎（NEC）。 NEC 是一种灾难性并发症，威胁脆弱早产儿的生命，但预防和早期识别实践（例如优先使用母乳、采用标准化喂养方案、输血和抗生素管理）的采用和 NEC 发生率差异很大。父母在 NEC 预防中发挥着关键作用（例如提供母亲自己的乳汁），但迄今为止，作为合作伙伴的参与不够。 NEC 占美国新生儿重症监护病房 (NICU) 费用的 20%，它在医院产后过程中发展较晚，并且可能突然发作，但到目前为止，还没有可用的工具来指导早期 NEC 识别。为了满足这一需求，我们的团队衍生并验证了名为 GutCheckNEC 的 NEC 风险决策规则，以准确区分 NEC。事实证明，使用临床决策支持 (CDS) 将预防实践整合到临床工作流程中可以提高跨环境下对推荐护理的依从性。然而，CDS 在新生儿重症监护病房 (NICU) 中的使用和评估都很稀少，据我们所知，尚无与 CDS 支持预防 NEC 相关的研究。根据实施科学的将研究转化为实践 (TRIP) 框架，在两个采用间断时间序列设计的 NICU 中，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、新生儿营养的效果以及家长的满意度。核心假设是，使用 CDS 进行时，对指南推荐的 NEC 预防和早期识别实践（称为“NEC-零”并使用依从性评分进行评估）的遵守率将会提高，并且 NEC 疾病将会下降。首先，将使用根据与当地临床医生的访谈构建的工作流程图来描述临床医生的工作流程，并将 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 NEC 场景和迭代评估，优化 NEC-Zero 可用性（目标 2）。最后，通过对NEC-Zero实施前1年和实施后1年的指标进行间断时间序列分析，我们将比较NEC疾病、新生儿营养和家长满意度结果的趋势；然后描述 NEC-零后临床医生 CDS 结果（依从性评分、使用反应率、满意度、对 CDS 意外后果的感知）与 NEC 疾病结果（目标 3）之间的关系。在 Daniel Malone 博士、RPh 和共同导师 Robert Greenes 医学博士、博士的指导下进行的可用临床决策支持的正式培训将补充由 Drs 指导的实施科学理论和方法的培训。玛丽塔·蒂特勒和梅兰妮·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 NICU 的其他临床挑战，以进行多方面的干预，以实现该研究计划的目标，即降低新生儿并发症的发病率和死亡率并限制成本。