DECISION SUPPORT FOR NEONATAL INTENSIVE CARE NURSING

长期目标是提高护理质量和成本效益的护理提供给早产儿在新生儿重症监护病房（NICU）通过提供一个自动化的知识为基础的系统，旨在增加他们的做法。目的是确定决策支持环境的核心特征，以解决由各种具有趋同和分歧价值观的从业人员在临床环境中做出决策的主观概率所照顾的一系列患者问题。这些活动旨在开发一个原型决策支持系统（DSS），供新生儿护理从业人员（NNP）和新生儿科医生在新生儿重症监护室使用。确定早产儿是否准备好口服喂养的问题将为本研究提供初步的临床重点。民族志和关键决策方法将用于阐明从业者的主观估计如何确定准备在早产儿口服喂养是作出的。内容分析将用于验证，如果适用的话，还将用于向模型添加新的决策策略。贝叶斯层次分析法将用于不确定阶段。将使用多属性实用技术（MAUT）进行偏好分析。一旦决策模型被构建，有效性测试将由一个国家专家小组执行。接下来，将构建决策支持系统（DSS）的原型系统。决策模型和附带的决策支持系统将在最初的研究地点进行准确性、效率和用户接受度的测试。决策模型和决策支持系统将在一些不同的医院进行现场测试，以确定其普遍性。最后，将该过程用于第二个临床问题，不仅可以测试与临床问题相关的泛化性，还可以帮助确定决策建模过程的哪些元素可以推广到护理实践的其他领域。未来的目标将是比较使用传统技术的实践和使用决策分析模型（纳入DSS）的实践增强，以辨别对患者结果和资源使用的影响。

The long term objective is to enhance the quality of care and cost-effectiveness of care provided to preterm infants in the neonatal intensive care unit (NICU) by providing health care practitioners with an automated knowledge-based system designed to augment their practice. The aim is to ascertain the core features of decision support environment for a nontrivial set of patient problems in patients cared for by a variety of practitioners with convergent and divergent values and subjective probabilities for decision making in a clinical setting. These activities are aimed at developing a prototype decision support system (DSS) for use by neonatal nurse practitioners (NNP)s and neonatologists in the NICU. The problem of determination of readiness for oral feeding in the preterm infant will provide the initial clinical focus for this research. Ethnography and the Critical Decision Method will be used to elucidate practitioners subjective estimates of how the determination of readiness for oral feedings in the preterm infant is made. A content analysis will be used to validate and, if applicable, to add new decision strategies to the model. Bayesian hierarchical analyses will be used for the uncertainty phase. A Multiattribute Utility Technique (MAUT) will be used to conduct preference analyses. Once the decision model has been structured, validity testing will be performed by a national panel of experts. Next, a prototype Decision Support System (DSS) system will be built. The decision-making model and the accompanying DSS will be tested for accuracy, efficiency and user acceptance at the initial research site. The decision-making model and DSS will be field tested for generalizability in a number of different hospitals. Finally, use of the process for a second clinical problem will be undertaken to test not only generalizability as it relates to a clinical problems, but also can help determine which elements of the decision modeling process can be generalized to other areas of nursing practice. A future goal will be to compare practice using traditional techniques and practice augmented using a decision-analytic model incorporated into a DSS to discern the effect on patient outcomes and resource use.