Kinney E L
Comput Biomed Res. 1986 Oct;19(5):462-7. doi: 10.1016/0010-4809(86)90040-6.
Although drug interactions (DI) are a common cause of morbidity, their large number precludes remembering them. To address this problem, we constructed a microcomputer-based expert system and assessed its efficacy in 90 consecutive inpatients. It was found that, without the expert system, a knowledge of the patient's medication list did not affect the frequency of occurrence of DI. Also, without the expert system, no DI were predicted, clinically, whereas the expert system predicted 27 DI of which, in retrospect, 10 actually occurred. Unsuspected DI were most likely if: a drug was not within the specialty of the clinician, DI host factors were present, or the DI involved a commonly prescribed drug pair. Although none of the drug interactions were life-threatening, in two cases, the DI was the cause for admission. Since the offending medications could usually be adjusted in dose, drug interactions were easily corrected once clinicians were made aware of them.
尽管药物相互作用（DI）是发病的常见原因，但因其数量众多，难以全部记住。为解决这一问题，我们构建了一个基于微型计算机的专家系统，并对90例连续住院患者评估了其疗效。结果发现，在没有专家系统的情况下，了解患者的用药清单并不会影响药物相互作用的发生频率。此外，在没有专家系统时，临床上未预测到任何药物相互作用，而专家系统预测到了27例药物相互作用，经回顾，其中10例实际发生。在以下情况下，未被怀疑的药物相互作用最有可能出现：药物不在临床医生的专业范围内、存在药物相互作用宿主因素，或药物相互作用涉及常用的药物组合。虽然所有药物相互作用均未危及生命，但在两例中，药物相互作用是入院的原因。由于通常可以调整致病药物的剂量，一旦临床医生意识到药物相互作用，就很容易纠正。
