INTELLIGENT CRITIQUING OF CLINICAL-GUIDELINE APPLICATION

临床指南是规范和统一提高医疗质量的有力手段。 在拟议的研究项目中，我们称之为Asgaard/DeGel，我们将设计和实施软件解决方案，以支持设计，应用，特别是护理提供者对临床指南应用的质量评估。 我们的长期目标包括提供一个标准化的计算框架的规范，应用程序和运行时间以及回顾性质量评估的临床指南。 我们将提供这些解决方案，通过使用一个新的框架规范和解释的临床指南。 新框架明确编码了指南所指示的治疗行动以及指南设计者的中间临床过程和结果目标，我们称之为意图。 意图被表示为时间模式的护理提供者的行动或患者的状态，以保持，实现或避免，使用我们以前的工作结果的解释和总结的时间为导向的临床数据。 意图包括要遵循的中间和总体过程模式（护理提供者行动）以及预期的中间和最终结果模式（患者状态）。 我们关注的任务包括（1）设计时任务，如指南的规范，验证和验证，以及（2）运行时任务，如对指南应用的自动支持，从他们的行动中识别护理提供者的意图，以及对护理提供者应用指南的实时和回顾性批评和质量评估，考虑到指南及其意图，患者的医疗记录，以及对护理提供者感知意图的分析。 在我们以前的工作中，我们已经设计了一个正式的，机器可解释的语言，称为Asbru，表示和注释的基础上，我们的框架的指导方针，并实现了一个小的原型解释器。我们将实现一个完整的解释器Asbru语言和一套软件工具的规范，验证和验证的Asbru指导方针。 我们还将设计和实施一套计算方法，用于运行时（应用期间）和回顾性质量评估的临床指南应用，无论是对个体患者还是对患者群体，使用我们的基于意图的模型。 我们将严格测试，验证和评估我们的方法，使用临床领域的合作者，如肿瘤学，高血压和内分泌学。

Clinical guidelines are a powerful method for standardization and uniform improvement of the quality of medical care. In the proposed research project, which we call Asgaard/DeGel, we will design and implement software solutions that support the design, application, and, in particular, quality assessment of the application of clinical guidelines by care providers. Our long-term objectives include provision of a standardized computational framework for specification, application, and runtime as well as retrospective quality assessment of clinical-guidelines. We will provide these solutions by using a novel framework for specification and interpretation of clinical guidelines. The new framework encodes explicitly both the therapeutic actions indicated by the guideline and the intermediate clinical process and outcome goals of the guideline designers, which we refer to as intentions. Intentions are represented as temporal patterns of care-provider actions or patient states to be maintained, achieved or avoided, using results from our previous work on interpretation and summarization of time-oriented clinical data. Intentions include both the intermediate and overall process pattern (care provider actions) to follow and the expected intermediate and final outcome pattern (patient states). The tasks that we are focusing on include (1) design-time tasks, such as specification, validation, and verification of the guideline, and (2) runtime tasks such as automated support to application of the guideline, recognition of care providers' intentions from their actions, and real-time as well as retrospective critiquing and quality assessment of care providers' application of he guideline, given the guideline and its intentions, the patient's medical record, and the analysis of the care provider's perceived intentions. In our previous work, we have designed a formal, machine-interpretable language, called Asbru, to represent and to annotate guidelines based on our framework, and implemented a small prototype interpreter for it. We will implement a full interpreter for the Asbru language and a set of software tools for specification, validation, and verification of Asbru guidelines. We will also design and implement a set of computational methods for runtime (during application) and retrospective quality assessment of clinical guideline application, both for individual patients and for populations of patients, using our intention-based model. We will rigorously test, validate, and evaluate our methodologies using collaborators in clinical areas such as oncology, hypertension, and endocrinology.