Burke J P, Pestotnik S L
Department of Clinical Epidemiology and Infectious Diseases, LDS Hospital and University of Utah, Salt Lake City 84143, USA.
J Chemother. 1999 Dec;11(6):530-5. doi: 10.1179/joc.1999.11.6.530.
As part of our integrated hospital information system (the HELP system), we developed computer-assisted decision support programs for antimicrobial prescribing that are available at bedside terminals throughout our 520-bed community hospital. Recently, options have been added to allow direct physician order entry of anti-infective agents in the shock-trauma intensive care unit (STRICU). Physicians prescribed the computer-suggested regimens for 46% but followed the suggested dose and interval for 93% of the orders during a 1-year study period. In comparison to a 2-year pre-intervention period, improved drug selection and reductions in adverse drug events and costs were seen. Antimicrobial resistance patterns for nosocomial gram-negative isolates remained stable or improved in the STRICU over an 11-year period of computer-assisted antibiotic management. We conclude that strategies for optimizing antimicrobial prescribing have the potential to stabilize resistance and reduce costs by encouraging heterogeneous prescribing patterns, use of local antimicrobial susceptibility patterns to inform empiric drug selection, and reduced "tonnage" of antibiotic use.
作为我们综合医院信息系统(HELP系统)的一部分,我们开发了用于抗菌药物处方的计算机辅助决策支持程序,这些程序可在我们拥有520张床位的社区医院的床边终端使用。最近,又增加了一些选项,以便在休克创伤重症监护病房(STRICU)中医生能够直接在计算机上输入抗感染药物的医嘱。在为期1年的研究期间,医生采用了计算机建议方案的比例为46%,但93%的医嘱遵循了建议的剂量和用药间隔。与干预前的两年期相比,药物选择得到了改善,药物不良事件和成本有所降低。在为期11年的计算机辅助抗生素管理期间,STRICU中医院内革兰氏阴性菌分离株的耐药模式保持稳定或有所改善。我们得出结论,优化抗菌药物处方的策略有可能通过鼓励多样化的处方模式、利用当地抗菌药物敏感性模式指导经验性药物选择以及减少抗生素使用“量”来稳定耐药性并降低成本。