Reichley Richard M, Seaton Terry L, Resetar Ervina, Micek Scott T, Scott Karen L, Fraser Victoria J, Dunagan W Claiborne, Bailey Thomas C
Center for Healthcare Quality and Effectiveness, BJC Healthcare and Department of Medicine, Washington University School of Medicine, USA.
J Am Med Inform Assoc. 2005 Jul-Aug;12(4):383-9. doi: 10.1197/jamia.M1783. Epub 2005 Mar 31.
A commercial rule base (Cerner Multum) was used to identify medication orders exceeding recommended dosage limits at five hospitals within BJC HealthCare, an integrated health care system. During initial testing, clinical pharmacists determined that there was an excessive number of nuisance and clinically insignificant alerts, with an overall alert rate of 9.2%. A method for customizing the commercial rule base was implemented to increase rule specificity for problematic rules. The system was subsequently deployed at two facilities and achieved alert rates of less than 1%. Pharmacists screened these alerts and contacted ordering physicians in 21% of cases. Physicians made therapeutic changes in response to 38% of alerts presented to them. By applying simple techniques to customize rules, commercial rule bases can be used to rapidly deploy a safety net to screen drug orders for excessive dosages, while preserving the rule architecture for later implementations of more finely tuned clinical decision support.
在综合医疗保健系统BJC医疗保健公司旗下的五家医院中,使用了一个商业规则库(Cerner Multum)来识别超出推荐剂量限制的用药医嘱。在初始测试期间,临床药剂师确定存在过多烦扰性且临床意义不大的警报,总体警报率为9.2%。实施了一种定制商业规则库的方法,以提高有问题规则的特异性。该系统随后在两家机构进行了部署,警报率降至1%以下。药剂师对这些警报进行了筛查,并在21%的案例中联系了开医嘱的医生。医生针对向他们提出的警报中的38%做出了治疗调整。通过应用简单的技术来定制规则,商业规则库可用于快速部署一个安全网,以筛查过量用药医嘱,同时保留规则架构以便日后实施更精细调整的临床决策支持。