Hadzikadic M, Harrington A L, Bohren B F
Department of Orthopedic Surgery, Medical Informatics Center, Carolinas Medical Center, Charlotte, NC 28232, USA.
Medinfo. 1995;8 Pt 2:1589.
This paper addresses three key issues facing developers of clinical and/or research medical information systems. 1. INFORMATION. The basic function of every database is to store information about the phenomenon under investigation. There are many ways to organize information in a computer; however only a few will prove optimal for any real life situation. Computer Science theory has developed several approaches to database structure, with relational theory leading in popularity among end users [8]. Strict conformance to the rules of relational database design rewards the user with consistent data and flexible access to that data. A properly defined database structure minimizes redundancy i.e.,multiple storage of the same information. Redundancy introduces problems when updating a database, since the repeated value has to be updated in all locations--missing even a single value corrupts the whole database, and incorrect reports are produced [8]. To avoid such problems, relational theory offers a formal mechanism for determining the number and content of data files. These files not only preserve the conceptual schema of the application domain, but allow a virtually unlimited number of reports to be efficiently generated. 2. INTELLIGENCE. Flexible access enables the user to harvest additional value from collected data. This value is usually gained via reports defined at the time of database design. Although these reports are indispensable, with proper tools more information can be extracted from the database. For example, machine learning, a sub-discipline of artificial intelligence, has been successfully used to extract knowledge from databases of varying size by uncovering a correlation among fields and records[1-6, 9]. This knowledge, represented in the form of decision trees, production rules, and probabilistic networks, clearly adds a flavor of intelligence to the data collection and manipulation system. 3. INTERFACE. Despite the obvious importance of collecting data and extracting knowledge, current systems often impede these processes. Problems stem from the lack of user friendliness and functionality. To overcome these problems, several features of a successful human-computer interface have been identified [7], including the following "golden" rules of dialog design [7]: consistency, use of shortcuts for frequent users, informative feedback, organized sequence of actions, simple error handling, easy reversal of actions, user-oriented focus of control, and reduced short-term memory load. To this list of rules, we added visual representation of both data and query results, since our experience has demonstrated that users react much more positively to visual rather than textual information. In our design of the Orthopaedic Trauma Registry--under development at the Carolinas Medical Center--we have made every effort to follow the above rules. The results were rewarding--the end users actually not only want to use the product, but also to participate in its development.
本文探讨了临床和/或研究医学信息系统开发者面临的三个关键问题。1. 信息。每个数据库的基本功能是存储有关所研究现象的信息。在计算机中有多种组织信息的方式;然而,只有少数几种方式在任何实际情况中都将被证明是最优的。计算机科学理论已经开发出了几种数据库结构方法,其中关系理论在终端用户中最受欢迎[8]。严格遵守关系数据库设计规则能为用户提供一致的数据以及对该数据的灵活访问。正确定义的数据库结构可将冗余(即相同信息的多次存储)降至最低。在更新数据库时,冗余会引发问题,因为重复的值必须在所有位置进行更新——哪怕遗漏一个值都会破坏整个数据库,并产生错误的报告[8]。为避免此类问题,关系理论提供了一种确定数据文件数量和内容的形式化机制。这些文件不仅保留了应用领域的概念模式,还能高效生成几乎无限数量的报告。2. 智能。灵活访问能让用户从收集到的数据中获取额外价值。这种价值通常通过在数据库设计时定义的报告来获得。尽管这些报告必不可少,但借助适当的工具,可以从数据库中提取更多信息。例如,机器学习作为人工智能的一个子领域,已成功用于通过揭示字段和记录之间的相关性,从不同规模的数据库中提取知识[1 - 6, 9]。以决策树、产生式规则和概率网络形式表示的这些知识,显然为数据收集和处理系统增添了智能色彩。3. 用户界面。尽管收集数据和提取知识显然很重要,但当前系统常常阻碍这些过程。问题源于缺乏用户友好性和功能性。为克服这些问题,已确定了成功的人机界面的几个特征[7],包括以下对话设计的“黄金”规则[7]:一致性、为频繁用户使用快捷方式、提供信息反馈、有组织的操作顺序、简单的错误处理、操作易于撤销、以用户为导向的控制焦点以及减轻短期记忆负担。在这份规则清单中,我们增加了数据和查询结果的可视化表示,因为我们的经验表明,用户对可视化信息的反应比对文本信息的反应要积极得多。在我们对卡罗莱纳医疗中心正在开发的骨科创伤登记系统的设计中,我们已尽一切努力遵循上述规则。结果是令人满意的——最终用户实际上不仅想使用该产品,还想参与其开发。