SOFTWARE ARCHITECTURE FOR GUIDELINE DIRECTED THERAPY

我们建议开发一种新的计算机体系结构， 基于协议的护理的自动推理。我们将建立在我们的 具有开发ONCOCIN和T-HELPER系统的经验， 创建一套高度集成的计算机程序， 大大简化了新的自动化系统的建设， 了解临床协议和指南，以进行电子解释 存储患者数据并监测患者管理。我们的方法将 允许广泛的临床信息系统确定何时 临床实践指南和方案可能适用于特定患者， 根据这些指导方针推荐治疗，并对 患者护理偏离推荐的实践模式。的目标 我们的研究是解决现有自动化系统的根本缺陷， 通过开发新的数据， 模型，可以捕捉必要的时间差异， 数据和新的解决问题的方法，推理有关准则， 定向治疗 我们的研究计划包括四个步骤， 具体目标。(1)我们将创建一个医学概念的领域模型， 足以代表临床医学所需的要素， 在医学的三个领域中基于协议的护理的子集：肿瘤学，HIV 感染和高血压。(2)我们将创建一个临时数据管理 一种自动从以下内容中导出时间相关抽象的系统 主要临床数据。这个系统将支持一个新的数据库查询 一种允许软件客户端查询 除了主要的临床数据外， 数据本身。(3)我们将开发几个可扩展的问题解决 基于协议的护理方法，将在三个 我们将探索的临床领域。这些方法将自动化 治疗计划的任务，确定患者是否符合 协议和指南，以及批评提供者的管理 患者在使用指南时。(4)我们将评估 我们的问题解决架构对不同类别的适用性 临床方案。我们将把我们的架构重新整合到T-HELPER中 医疗工作站，并将测试架构的能力，以支持 三种临床应用指南和方案的推理 我们将探索的领域。 在我们的工作结束时，我们将开发一个经过验证的软件 可以支持临时数据管理和自动化的体系结构 对复杂的临床方案和指南进行推理。因为我们的 我们致力于UNIX、C、TCP/IP和SQL等行业标准， 该系统将作为一个开放式“服务器”，用于临时数据管理 在各种应用程序中。

We propose to develop a novel computer architecture that will support automated reasoning about protocol-based care. We will build on our previous experience in developing the ONCOCIN and T-HELPER systems to create a highly integrated set of computer programs that will significantly ease the construction of new automated systems that can use knowledge of clinical protocols and guidelines to interpret electronically stored patient data and to monitor patient management. Our approach will allow a wide range of clinical information systems to determine when clinical practice guidelines and protocols may apply to given patients, to recommend therapy in accordance with those guidelines, and to critique patient care that deviates from recommended practice patterns. The goal of our research is to address fundamental deficiencies in existing automated approaches to guideline-directed therapy by developing both new data models that can capture the necessary temporal distinctions in patient data and new problem-solving methods for reasoning about guideline- directed therapy. Our research plan consists of a four-step process that defines our specific aims. (1) We will create a domain model of medical concepts that is sufficient to represent the elements of clinical medicine required for a subset of protocol-based care in three areas of medicine: oncology, HIV infection, and hypertension. (2) We will create a temporal data management system that will derive automatically time-related abstractions from primary clinical data. This system will support a new database query language that will allow software clients to query for the presence of time-related abstractions in clinical data, in addition to the primary data themselves. (3) We will develop several extensible problem-solving methods for protocol-based care that will be reusable within the three clinical domains that we will explore. These methods will automate the tasks of therapy planning, of determining patient eligibility for protocols and guidelines, and of critiquing provider's management of patients when practice guidelines apply. (4) We will evaluate the applicability of our problem-solving architecture to different classes of clinical protocols. We will reintegrate our architecture into the T-HELPER medical workstation, and will test the architecture's ability to support reasoning about guidelines and protocols in the three clinical application areas that we will explore. At the conclusion of our work, we will have developed a validated software architecture that can support temporal-data management and automated reasoning about complex clinical protocols and guidelines. Because of our commitment to industry standards such as UNIX, C, TCP/IP, and SQL, our system will be usable as an open "server" for temporal-data management within a variety of application programs.