Elson R B, Connelly D P
Division of Health Computer Sciences, University of Minnesota, Minneapolis, USA.
Prim Care. 1995 Jun;22(2):365-84.
Computerized decision support can be passive or active. Passive decision support occurs when a computer facilitates access to relevant patient data or clinical knowledge for interpretation by the physician. Examples include CPR systems and reference texts or literature databases on CD-ROM. Effective passive decision support may ultimately prove to have a significant impact on physician decision making, but its potential to do so has been largely unexplored. Active decision support implies some higher level of information processing, or inference, by the computer. Examples include reminder / alert systems and diagnostic decision support systems. Inference processing in active decision support systems is generally rule-based, but probabilistic inference has been successfully used as well. Reminder systems have been consistently demonstrated to improve dramatically physician guideline compliance, generally by reducing oversight or error. The same potential for large-scale, systematic impact on physician decision-making by diagnostic decision support systems probably does not exist, but these systems may prove to be extremely useful in individual cases. Current applicability of diagnostic decision support systems to primary care is limited by the incompleteness and inaccuracies of the knowledge bases of these systems with respect to primary care. The applicability of computerized decision support in general to primary care is limited by more practical considerations. Widespread computerized decision support will not occur without CPR systems coupled with appropriate data standards and nomenclatures that will permit decision support tools to be accessed effortlessly during the routine process of patient care.
计算机化决策支持可以是被动的或主动的。当计算机便于获取相关患者数据或临床知识以供医生解读时,就会出现被动决策支持。示例包括心肺复苏系统以及光盘上的参考文本或文献数据库。有效的被动决策支持最终可能会被证明对医生的决策产生重大影响,但其这样做的潜力在很大程度上尚未得到探索。主动决策支持意味着计算机进行某种更高层次的信息处理或推理。示例包括提醒/警报系统和诊断决策支持系统。主动决策支持系统中的推理处理通常基于规则,但概率推理也已得到成功应用。提醒系统一直被证明能显著提高医生对指南的依从性,通常是通过减少疏忽或错误来实现的。诊断决策支持系统对医生决策产生大规模、系统性影响的潜力可能不存在,但这些系统在个别病例中可能会被证明极其有用。目前,诊断决策支持系统在初级保健中的适用性受到这些系统关于初级保健的知识库的不完整性和不准确之处的限制。一般而言,计算机化决策支持在初级保健中的适用性受到更多实际因素的限制。如果没有心肺复苏系统以及适当的数据标准和术语,就不会出现广泛的计算机化决策支持,而这些标准和术语将使决策支持工具在患者护理的常规过程中能够轻松获取。