Moja Lorenzo, Kwag Koren H, Lytras Theodore, Bertizzolo Lorenzo, Brandt Linn, Pecoraro Valentina, Rigon Giulio, Vaona Alberto, Ruggiero Francesca, Mangia Massimo, Iorio Alfonso, Kunnamo Ilkka, Bonovas Stefanos
Lorenzo Moja is with the Department of Biomedical Sciences for Health, University of Milan, and the Unit of Clinical Epidemiology, IRCCS Orthopedic Institute Galeazzi, Milan, Italy. Koren H. Kwag is with the Unit of Clinical Epidemiology, IRCCS Orthopedic Institute Galeazzi, Milan. Theodore Lytras is with the Department of Epidemiological Surveillance and Intervention, Hellenic Centre for Disease Control and Prevention, Athens, Greece, the Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain, and the Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona. Lorenzo Bertizzolo and Francesca Ruggiero are with the Department of Biomedical Sciences for Health, University of Milan. Linn Brandt is with the Department of Internal Medicine, Inland Hospital Trust, Oslo, Norway, the Department of Internal Medicine, Diakonhjemmet Hospital, Oslo, and HELSAM, University of Oslo. Valentina Pecoraro is with the University of Milan. Giulio Rigon and Alberto Vaona are with Azienda ULSS 20, Verona, Italy. Massimo Mangia is with Medilogy SRL, Milan. Alfonso Iorio is with the Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ontario. Ilkka Kunnamo is with Duodecim Medical Publications Ltd, Helsinki, Finland. Stefanos Bonovas is with the Laboratory of Drug Regulatory Policies, IRCCS Mario Negri Institute for Pharmacological Research, Milan, and the Department of Pharmacology, School of Medicine, University of Athens, Athens.
Am J Public Health. 2014 Dec;104(12):e12-22. doi: 10.2105/AJPH.2014.302164. Epub 2014 Oct 16.
We systematically reviewed randomized controlled trials (RCTs) assessing the effectiveness of computerized decision support systems (CDSSs) featuring rule- or algorithm-based software integrated with electronic health records (EHRs) and evidence-based knowledge. We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and Cochrane Database of Abstracts of Reviews of Effects. Information on system design, capabilities, acquisition, implementation context, and effects on mortality, morbidity, and economic outcomes were extracted. Twenty-eight RCTs were included. CDSS use did not affect mortality (16 trials, 37395 patients; 2282 deaths; risk ratio [RR] = 0.96; 95% confidence interval [CI] = 0.85, 1.08; I(2) = 41%). A statistically significant effect was evident in the prevention of morbidity, any disease (9 RCTs; 13868 patients; RR = 0.82; 95% CI = 0.68, 0.99; I(2) = 64%), but selective outcome reporting or publication bias cannot be excluded. We observed differences for costs and health service utilization, although these were often small in magnitude. Across clinical settings, new generation CDSSs integrated with EHRs do not affect mortality and might moderately improve morbidity outcomes.
我们系统回顾了随机对照试验（RCT），以评估计算机化决策支持系统（CDSS）的有效性，这些系统具有与电子健康记录（EHR）和循证知识相结合的基于规则或算法的软件。我们检索了MEDLINE、EMBASE、Cochrane对照试验中央注册库和Cochrane系统评价摘要数据库。提取了有关系统设计、功能、获取、实施背景以及对死亡率、发病率和经济结果影响的信息。纳入了28项随机对照试验。使用CDSS不影响死亡率（16项试验，37395例患者；2282例死亡；风险比[RR]=0.96；95%置信区间[CI]=0.85，1.08；I²=41%）。在预防任何疾病的发病率方面有显著统计学意义（9项试验；13868例患者；RR=0.82；95%CI=0.68，0.99；I²=64%），但不能排除选择性结果报告或发表偏倚。我们观察到成本和卫生服务利用方面存在差异，尽管这些差异通常较小。在各种临床环境中，与电子健康记录相结合的新一代CDSS不影响死亡率，可能会适度改善发病率结果。
