COMPUTER ASSISTED PATIENT INTERVIEWING IN CLINICAL PHARMACY

临床药师应对药物信息爆炸， 更直接地参与病人护理。 具体来说，临床 药剂师在配药方面变得越来越活跃 向患者提供信息，检查患者对 给药方案、筛选单一药物引起的不良反应 和药物组合，并找出可能的并发症之间 药物和食物，过敏和慢性疾病。 一 计算机系统实验室和 和临床中心药学部设计和开发一个 一个可以直接访问病人的计算机系统， 用药史和标记可能的不良反应相关 医疗团 据信，这种“病人友好”的系统， 如果成功，就可以真正“克隆”临床药师的技能。 一 计算机访问系统可以容纳许多病人，使更多的 药剂师时间可用于不适合的患者 直接电脑面试 CSL面试系统 患者征求药物治疗方案，医疗条件和症状， 服药依从性、饮食史、职业和环境 毒性暴露和评估药物不良反应所需的其他信息 反应（ADR）或相互作用。 在自动面试结束时， 该系统为主治医师产生简明报告。 今年，美国药典会议药物信息 数据库被选择用于访谈系统。 因为 数据库包含外行术语中的不良临床影响，它使 我们需要建立一个非专业术语词库，以获取药物信息。 USP希望使用同义词词典来标准化不良反应术语 并消除用于描述相同效果的冗余术语。 CSL也 开发了一个机器学习的ADR检测和评估方案， 德尔菲调查结果来自10名临床药师， 融入面试系统。

Clinical pharmacists are responding to the drug information explosion by participating more directly in patient care. Specifically, clinical pharmacists have become increasingly active in dispensing pharmaceutical information to patients, checking for patient compliance with their medication regimen, screening for adverse effects caused by single drugs and drug combinations, and sorting out possible complications between medications and food, allergies and chronic medical conditions. A collaborative project was initiated between the Computer Systems Laboratory and the Clinical Center Pharmacy Department to design and develop a computer system that could directly interview patients in order to collect medication histories and flag possible untoward effects related to medication regiments. It is believed that this "patient friendly" system, if successful, could truly "clone" the skills of clinical pharmacists. A computer interviewing system can accommodate many patients, making more pharmacist time available for patients who are not suitable candidates for direct computer interviewing. The system developed by CSL interviews patients to solicit medication regimen, medical conditions and symptoms, medication compliance, dietary history, occupational and environmental toxic exposure and other information needed to assess adverse drug reactions (ADRs) or interactions. At the end of the automated interview, the system produces a concise report for the attending physician. This year, the United States Pharmacopeial Convention Drug Information database was chosen for use with the interviewing system. Because the database contains adverse clinical effects in lay terminology, it enabled us to develop a lay terminology thesaurus to access the drug information. USP expects to use the thesaurus to standardize adverse effects terminology and eliminate redundant terms for describing the same effect. CSL also developed a machine-learned ADR detection and evaluation scheme using Delphi polling results obtained from 10 clinical pharmacists that is being integrated into the interviewing system.