COMPUTER-BASED PROSPECTIVE DRUG UTILIZATION REVIEW

基于计算机的前瞻性药物利用审查

• 批准号: 2236237
• 负责人: WILLIAM M. TIERNEY
• 金额: $ 49.36万
• 依托单位: INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
• 依托单位国家: 美国
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-07-01 至 1997-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2236237
• 关键词: COMPUTER; BASED; PROSPECTIVE; DRUG; UTILIZATION

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.

药物利用审查（DUR）已迅速成为质量的主要焦点