Lau F, Vincent D D
Department of Applied Sciences in Medicine, University of Alberta, Edmonton, Canada.
Comput Biomed Res. 1993 Jun;26(3):294-309. doi: 10.1006/cbmr.1993.1020.
The massive volume of hemodynamic data routinely available within the Cardiovascular Intensive Care Unit (CVICU) can adversely affect the quality, relevance, and timing of hemodynamic management decisions on patients after cardiac surgery. Yet, at the same time, the lack of appropriate treatment-outcome data and access to prior CV case histories deprives the clinician of any opportunity to improve personal decision-making skill and assess the effectiveness of various treatment methods. This paper presents a formalized decision-support model for CVICU that incorporates expert and quantitative knowledge, as well as prior outcome and case experience to augment the clinician's decision-making capability. This includes the use of optimal hemodynamic patterns derived from outcome analysis as therapy goals, expert rules and trend analysis to interpret incoming data, standardized protocols based on predefined hemodynamic patterns from clinical cases, and access to the database for similar case comparison. Most importantly, the model suggests an integrated approach where the clinical database not only is a documentation source for the patient, but also can serve as an outcome research database where clinical experience can be formalized and combined with expert knowledge to influence future therapy decisions. At present, a prototype is being developed at the CVICU of the University of Alberta Hospitals on a Unix platform using ART-IM, C and Ingres. Once implemented, the prototype will be evaluated on a small group of CV patients for its effectiveness and acceptability to clinicians.
心血管重症监护病房(CVICU)中常规可获取的大量血流动力学数据,可能会对心脏手术后患者血流动力学管理决策的质量、相关性和及时性产生不利影响。然而,与此同时,缺乏适当的治疗结果数据以及无法获取既往CV病例史,使临床医生失去了提高个人决策技能和评估各种治疗方法有效性的任何机会。本文提出了一种针对CVICU的形式化决策支持模型,该模型整合了专家知识和定量知识,以及既往结果和病例经验,以增强临床医生的决策能力。这包括将从结果分析中得出的最佳血流动力学模式用作治疗目标,运用专家规则和趋势分析来解读输入数据,基于临床病例中预定义的血流动力学模式制定标准化方案,以及访问数据库进行相似病例比较。最重要的是,该模型提出了一种综合方法,其中临床数据库不仅是患者的文档来源,还可以作为结果研究数据库,在该数据库中临床经验可以形式化,并与专家知识相结合以影响未来的治疗决策。目前,阿尔伯塔大学医院CVICU正在Unix平台上使用ART-IM、C和Ingres开发一个原型。一旦实施,将对一小部分CV患者评估该原型对临床医生的有效性和可接受性。