Berlin Amy, Sorani Marco, Sim Ida
Department of Psychiatry, University of California-San Francisco, 3333 California Street, San Francisco, CA 94143, USA.
Stud Health Technol Inform. 2004;107(Pt 1):578-81.
Computer-based clinical decision support systems (CDSSs) have been championed for their potential to improve health-care quality. However, there has been no systematic study of the types of CDSSs that have been developed. In previous work, we developed the CDSS Taxonomy for comprehensively describing the technical, workflow, and contextual characteristics of CDSSs. We now use the CDSS Taxonomy to describe outpatient CDSSs evaluated in randomized controlled trials published between 1998 and 2002. 31 studies comprising 42 CDSS systems were included in our analysis. The majority of systems used rule-based reasoning engines to "push" explicit, individualized recommendations concerning non-urgent decisions to clinicians or patients, but not both. 71% of the systems required someone to manually enter data into the system or to process the system output for use by the target decision maker. The average kappa for coding agreement was > 0.6. Our findings demonstrate that outpatient CDSSs vary greatly in design and function. Many impose a data entry or output-processing burden on clinic staff. More complete reporting of CDSS characteristics is needed in the literature.
基于计算机的临床决策支持系统(CDSS)因其改善医疗质量的潜力而备受推崇。然而,对于已开发的CDSS类型尚未有系统的研究。在之前的工作中,我们开发了CDSS分类法,用于全面描述CDSS的技术、工作流程和情境特征。我们现在使用CDSS分类法来描述在1998年至2002年期间发表的随机对照试验中评估的门诊CDSS。我们的分析纳入了31项研究,涵盖42个CDSS系统。大多数系统使用基于规则的推理引擎,针对非紧急决策向临床医生或患者“推送”明确的、个性化的建议,但并非同时向两者推送。71%的系统要求有人手动将数据输入系统或处理系统输出以供目标决策者使用。编码一致性的平均kappa值>0.6。我们的研究结果表明,门诊CDSS在设计和功能上差异很大。许多系统给诊所工作人员带来了数据输入或输出处理负担。文献中需要更完整地报告CDSS的特征。