COMPUTER-BASED PROSPECTIVE DRUG UTILIZATION REVIEW

药物利用审评(DUR)已迅速成为质量的主要焦点 医疗界内的医疗保健，并已成为主要的经济来源 联邦政府内部的利益。随着1990年《Obra》的颁布 各州被要求在1993年1月之前实施DUR方案。 DUR是一个通过比较实际情况来改进药物治疗的过程 根据预先确定的标准使用药物，并提供结果 这与给医生开处方进行了比较。DUR有两个基本的 研究方法：回顾和前瞻性研究。其中的每一个都有内在的 限制，但乐观的是，未来的DUR提供有效的 优势。目前缺乏对照试验来支持这一点。 乐观主义。印第安纳州先前对医生决策的研究 大学和雷根斯特里夫研究所建议，患者的特异性 在作出决定时向医疗保健提供者提供的提醒 正在进行的治疗可能会改善对治疗建议的遵从性。 这些提醒利用Regenstrief医疗记录中的患者数据 系统(RMRS)纵向、组合、住院和门诊 电子病历。合规性的改善一直是 示范预防护理提醒和实验室测试订购。 拟议的研究将在随机对照试验中检查 由基于规则的专家系统生成的提醒的效果 在开具处方时反馈给开处方的医生 在处方配药时写信或给药剂师。这个 专家系统将结合病情和患者的具体治疗 使用存储在中的先前记录的患者数据提出建议 RMR创建高度特定于患者的提醒。治疗标准 将根据科学文献和纲要开发，如 以及当地专家共识小组。此外，根据具体情况 将开发预测性模型和患者结局的概率 例如向医生提供的住院治疗是 反馈。三种目标状态(充血性心力衰竭、反应性 呼吸道疾病和冠状动脉疾病)用于DUR研究 因为它们代表了常见的、致残的和病态的疾病。第160位 在学术、内城、全科执业的内科医生 随机分为(1)常规护理(仅限于医院正在进行的 回顾DUR)；(2)医生目标预期DUR；(3) 以药剂师为目标的未来DUR；或(4)医生和 药剂师的目标是未来的DUR。500名患者每人 情况将每隔6个月确定并跟踪两次 好几年了。主要结果衡量标准将包括功能状态(SF-36 分数)、具体情况问题、患者对健康的满意度 护理(PSQ得分)，以及随后的药物依从性和 住院治疗。次要结果衡量标准将是医生和 药剂师对指南的遵从性、患者死亡率和 医疗保健费用。这个项目将具有相当大的探测能力 主要结果的差异。如果表现出积极的影响 患者的功能状态、对医疗保健的满意度或健康状况 护理利用，基于计算机的DUR将提供一种经济高效的工具 用于改善卫生保健服务的提供。

Drug utilization review (DUR) has rapidly become a major focus of quality of care within the medical community and has become a major financial interest within the federal government. With the enactment of OBRA 1990 individual states are mandated to implement DUR programs by January 1993. DUR is a process for improving pharmaceutical therapy by comparing actual drug use to established predetermined criteria and providing the results of this comparison to prescribing physicians. DUR has two basic approaches: retrospective and prospective. Each of these have inherent limitations, but optimism exists that prospective DUR offers efficacious advantages. Controlled trials are currently lacking to support this optimism. Previous research into physician decision making at Indiana University and the Regenstrief Institute suggests that patient specific reminders delivered to the health care provider at the time a decision is being made may improve compliance with treatment recommendations. These reminders utilize patient data from the Regenstrief Medical Record System (RMRS) a longitudinal, combined, in-patient and out-patient electronic medical record. Improvement in compliance has been demonstrated for preventive care reminders and laboratory test ordering. The proposed study will examine in a randomized controlled trial the effect of reminders generated by a rule-based, expert system which will be fed back to the prescribing physician at the time of prescription writing or to pharmacists at the time of prescription dispensing. The expert system will combine condition and patient specific treatment recommendations with previously recorded patient data which is stored in the RMRS to create highly patient specific reminders. Treatment criteria will be developed based ont he scientific literature and compendia as well as a local expert consensus panel. In addition, condition specific predictive models will be developed and probabilities of patient outcomes such as hospitalization provided to the physician as part of the feedback. Three target conditions (congestive heart failure, reactive airways disease, and coronary artery disease) were selected for DUR study because they represent common, disabling, and morbid diseases. The 160 physicians in an academic, inner city, general medicine practice will be randomized to (1) usual care (limited to the hospital's ongoing retrospective DUR); (2) physician targeted prospective DUR; (3) pharmacist targeted prospective DUR; or (4) combined physician and pharmacist targeted prospective DUR. Five hundred patients with each condition will be identified and followed at 6 month intervals for two years. Primary outcome measures will include functional status (SF-36 scores), condition specific questions, patient satisfaction with health care (PSQ scores), and subsequent medicine compliance and hospitalization. Secondary outcome measures will be physician and pharmacist compliance with guidelines, patient mortality, and direct health care costs. This project will have considerable power to detect differences in the primary outcomes. If shown to positively affect patients' functional status, satisfaction with health care, or health care utilization, a computer-based DUR will offer a cost-effective tool for improving health care delivery.