DECISION SUPPORT FOR NEONATAL INTENSIVE CARE NURSING

长期目标是通过为医疗保健从业人员提供旨在增强其实践的自动化知识系统，提高新生儿重症监护室（NICU）中早产儿的护理质量和成本效益。 我们的目的是确定决策支持环境的核心功能，为一个不平凡的一组病人的问题，由各种各样的从业者在临床环境中决策的收敛和发散的价值观和主观概率的患者照顾。 这些活动的目的是开发一个原型决策支持系统（DSS）的新生儿执业护士（NNP）和新生儿重症监护室的儿科医生使用。 早产儿经口喂养准备的确定问题将为这项研究提供最初的临床焦点。 民族志和关键决策方法将被用来阐明医生的主观估计如何确定准备在早产儿口服喂养。 内容分析将用于验证，并在适用的情况下为模型添加新的决策策略。 贝叶斯分层分析将用于不确定性阶段。 将使用多属性效用技术（MAUT）进行偏好分析。一旦决策模型结构化，将由一个国家专家小组进行有效性测试。 接下来，将建立一个原型决策支持系统（DSS）系统。将在最初的研究地点测试决策模式和配套的决策支持系统的准确性、效率和用户接受程度。 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的普遍性。最后，使用的过程中的第二个临床问题将进行测试，不仅因为它涉及到一个临床问题的可推广性，但也可以帮助确定哪些元素的决策建模过程可以推广到其他领域的护理实践。 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，以识别对患者结局和资源使用的影响。

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.