COMPUTER ASSISTED PATIENT INTERVIEWING IN CLINICAL PHARMACY

随着临床药师越来越多地参与直接的病人护理， 分发药物信息并帮助识别潜在药物 相互作用引起的健康危害，他们必须跟上新的药物 信息，为患者分配更多的一对一时间，并保持 有效的面试技巧。 为了支持这些活动，CSL开始 1990年与NIH临床中心药学部合作。 目标是开发一个计算机面试系统， 用药历史，向患者分发用药信息，以及 检测与药物治疗方案相关的可能的不良事件， 为非候选患者提供更多的药剂师时间 电脑面试。 该系统产生的数据可以帮助 专注于药剂师与患者的互动。 药物历史系统的初始版本开发，测试， 1991财年报告，包括患者的系统访谈脚本 人口统计学、健康史和药物使用。 一份简明的总结报告是 采访后制作的。 在1992财年，访谈脚本和药物不良反应（ADR）词库 进行了完善，并提供了一份按机构分类的描述ADR的综合报告 系统准备并提交给USP，以帮助标准化未来 ADR术语。 数据库模块的设计是为了支持不良药物 反应和药物-药物相互作用检测和程序被创建用于 患者药物信息和医师药物监测信息 检索 此外，神经网络模块的药物不良反应， 开发了一种检测方法，该方法比以前的 多层次系统评价方案。 完成并整合所有程序模块和数据库组件， 并开始正式测试和评估已完成的系统是 计划在FY 93。

As clinical pharmacists become more involved in direct patient care by dispensing medication information and helping to identify potential drug interaction-induced health hazards, they must keep abreast of new drug information, allocate more one-on-one time for patients, and maintain effective interviewing skills. In support of these activities, CSL began a collaboration in 1990 with the NIH Clinical Center Pharmacy Department. The objective was to develop a computer interviewing system that collects medication histories, dispenses medication information to patients, and detects possible untoward events related to medication regimens, thereby making more pharmacist time available for patients who are not candidates for computer interviewing. Warnings generated by this system could aid in focusing the pharmacist-patient interaction. The initial version of the medication history system developed, tested, and reported in FY91, included system interview scripts for patient demographics, health history, and drug usage. A concise summary report is produced after the interview. In FY92 the interview scripts and adverse drug reaction (ADR) thesaurus were refined and a comprehensive report describing ADR's sorted by body systems was prepared and submitted to USP to assist in standardizing future ADR terminology. Database modules were designed to support adverse drug reaction and drug-drug interaction detection and programs were created for patient drug information and physician drug monitoring information retrieval. Also, a neural network module for adverse drug reaction detection was developed that demonstrated improvement over a previous multi-level system evaluation scheme. Completion and integration of all program modules and database components, and initiation of formal testing and evaluation of the completed system are planned for FY93.