Séroussi B, Bouaud J, Antoine E C
Service d'Informatique Médicale, DSI/AP-HP & Département de Biomatiques, Université Paris 6, Paris, France.
Artif Intell Med. 2001 Apr;22(1):43-64. doi: 10.1016/s0933-3657(00)00099-3.
Originally published as textual documents, clinical practice guidelines have poorly penetrated medical practice because their editorial properties do not allow the reader to easily solve, at the point of care, a given medical problem. However, despite the proliferation of implemented clinical practice guidelines as decision support systems providing an easy access to patient-centered information, there is still little evidence of high physician compliance to guidelines recommendations. Apart from physicians' psychological reluctance, the incompleteness of guideline knowledge and the impreciseness of the terms used, another reason may be that, although suited to average patients, clinical practice guideline recommendations are not a substitute for the physician-controlled clinical judgement that should be applied to each actual individual patient. Therefore, computer-based approaches based on the automation of context-free operationalization of guideline knowledge, although providing uniform optimal strategies to problem-focused care delivery, may generate inappropriate inferences for a specific patient that the physician does not follow in practice. Rather than providing automated decision support, ONCODOC allows the clinician to control the operationalization of guideline knowledge through his hypertextual reading of a knowledge base encoded as a decision tree. In this way, he has the opportunity to interpret the information provided in the context of his patient, therefore, controlling his categorization to the closest matching formal patient. Experimented in life-size ONCODOC demonstrated good appropriation of the system by physicians with significantly high scores of compliance. We successfully tested the implemented strategy and the knowledge base in a second medical institution, giving then a noticeable example of reuse and sharing of encoded guideline knowledge across institutions.
临床实践指南最初以文本形式发布，在医学实践中的渗透程度较低，因为其编辑特性不允许读者在医疗现场轻松解决特定的医学问题。然而，尽管作为决策支持系统的临床实践指南大量涌现，能够方便地获取以患者为中心的信息，但几乎没有证据表明医生对指南建议的高依从性。除了医生的心理抵触、指南知识的不完整性以及所用术语的不精确性之外，另一个原因可能是，尽管临床实践指南建议适用于普通患者，但它们并不能替代医生针对每个实际个体患者应运用的临床判断。因此，基于指南知识的无上下文操作自动化的计算机方法，虽然为以问题为导向的护理提供了统一的最佳策略，但可能会对医生在实践中不遵循的特定患者产生不恰当的推断。ONCODOC并非提供自动化决策支持，而是允许临床医生通过对编码为决策树的知识库进行超文本阅读来控制指南知识的操作。通过这种方式，他有机会在其患者的背景下解释所提供的信息，从而将其分类到最匹配的正式患者类别。在实际规模的ONCODOC中进行的试验表明，医生对该系统的接受度良好，依从性得分显著较高。我们在第二家医疗机构成功测试了实施的策略和知识库，从而给出了一个跨机构重用和共享编码指南知识的显著示例。
