Thompson Gwen, O'Horo John C, Pickering Brian W, Herasevich Vitaly
1Division of General Internal Medicine, Mayo Clinic, Rochester, MN. 2Division of Infectious Diseases, Mayo Clinic, Rochester, MN. 3Multidisciplinary Epidemiology and Translational Research in Intensive Care and Department of Anesthesiology, Division of Critical Care Medicine, Mayo Clinic, Rochester, MN.
Crit Care Med. 2015 Jun;43(6):1276-82. doi: 10.1097/CCM.0000000000000948.
To evaluate effects of health information technology in the inpatient and ICU on mortality, length of stay, and cost. Methodical evaluation of the impact of health information technology on outcomes is essential for institutions to make informed decisions regarding implementation.
EMBASE, Scopus, Medline, the Cochrane Review database, and Web of Science were searched from database inception through July 2013. Manual review of references of identified articles was also completed.
Selection criteria included a health information technology intervention such as computerized physician order entry, clinical decision support systems, and surveillance systems, an inpatient setting, and endpoints of mortality, length of stay, or cost. Studies were screened by three reviewers. Of the 2,803 studies screened, 45 met selection criteria (1.6%).
Data were abstracted on the year, design, intervention type, system used, comparator, sample sizes, and effect on outcomes. Studies were abstracted independently by three reviewers.
There was a significant effect of surveillance systems on in-hospital mortality (odds ratio, 0.85; 95% CI, 0.76-0.94; I=59%). All other quantitative analyses of health information technology interventions effect on mortality and length of stay were not statistically significant. Cost was unable to be quantitatively evaluated. Qualitative synthesis of studies of each outcome demonstrated significant study heterogeneity and small clinical effects.
Electronic interventions were not shown to have a substantial effect on mortality, length of stay, or cost. This may be due to the small number of studies that were able to be aggregately analyzed due to the heterogeneity of study populations, interventions, and endpoints. Better evidence is needed to identify the most meaningful ways to implement and use health information technology and before a statement of the effect of these systems on patient outcomes can be made.
评估住院部及重症监护病房（ICU）中健康信息技术对死亡率、住院时长及费用的影响。对健康信息技术对治疗结果的影响进行系统评估，对于各机构在实施相关技术时做出明智决策至关重要。
检索了EMBASE、Scopus、Medline、Cochrane系统评价数据库及科学引文索引数据库，检索时间跨度从建库至2013年7月。同时还对已识别文章的参考文献进行了人工查阅。
选择标准包括健康信息技术干预措施，如计算机化医嘱录入、临床决策支持系统及监测系统；住院环境；以及死亡率、住院时长或费用等终点指标。由三名评审员对研究进行筛选。在筛选的2803项研究中，45项符合选择标准（1.6%）。
提取的数据包括年份、研究设计、干预类型、使用的系统、对照、样本量以及对治疗结果的影响。由三名评审员独立提取研究数据。
监测系统对院内死亡率有显著影响（优势比为0.85；95%置信区间为0.76 - 0.94；I² = 59%）。健康信息技术干预措施对死亡率和住院时长的所有其他定量分析均无统计学意义。费用无法进行定量评估。对各项结果研究的定性综合分析显示出显著的研究异质性及较小的临床效果。
电子干预措施未显示出对死亡率、住院时长或费用有实质性影响。这可能是由于研究人群、干预措施及终点指标的异质性，能够进行汇总分析的研究数量较少。在确定实施和使用健康信息技术的最有效方式以及说明这些系统对患者治疗结果的影响之前，需要更好的证据。
