文章基本信息

标题：Effectiveness of Computerized Decision Support Systems Linked to Electronic Health Records: A Systematic Review and Meta-Analysis
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作者：Lorenzo Moja ; Koren H. Kwag ; Theodore Lytras 等
期刊名称：American journal of public health
印刷版ISSN：0090-0036
出版年度：2014
卷号：104
期号：12
页码：e12-e22
DOI：10.2105/AJPH.2014.302164
语种：English
出版社：American Public Health Association
摘要：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. The quality of medical care is variable and often suboptimal across health care systems. 1 Despite the growing availability of knowledge from randomized controlled trials (RCTs) and systematic reviews to guide clinical practice, there remains a discrepancy in the application of evidence into health care services. 2 Current research demonstrates the potential of computerized decision support systems (CDSSs) to assist with problems raised in clinical practice, increase clinician adherence to guideline- or protocol-based care, and, ultimately, improve the overall efficiency and quality of health care delivery systems. 1,3,4 CDSSs have been additionally shown to increase the use of preventive care in hospitalized patients, facilitate communication between providers and patients, enable faster and more accurate access to medical record data, improve the quality and safety of medication prescribing, and decrease the rate of prescription errors. 5–9 A recent study estimated that the adoption of Computerized Physician Order Entry and Clinical Decision Support could prevent 100 000 inpatient adverse drug events (ADEs) per year, resulting in increased inpatient bed availability by more than 700 000 bed-days and opportunity savings approaching €300 million in the studied European Union member states (i.e., the Czech Republic, France, the Netherlands, Sweden, Spain, and the United Kingdom). 10 Electronic Health Records (EHRs) represent another innovation that is gaining momentum in health care systems. In the United States, the use of EHRs is encouraged by the $27 billion allocated in reimbursement incentives by the 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act. Under the Act, clinicians and hospitals must demonstrate “meaningful use” of EHRs by adhering to a set of criteria, which includes the implementation of clinical decision support rules relevant to a specialty or high priority hospital condition such as diagnostic test ordering. 11 The integration of CDSSs with EHRs through the delivery of guidance messages to health care professionals at the point of care may maximize the impact of both innovations. A primary barrier to successful CDSS evaluation is its broad definition adopted by the research community, which encompasses a diverse range of interventions and functions ( see the box on page e2 ). The inclusion of studies with variable interventions across diverse health care settings precluded systematic reviews from reaching a decisive understanding of the impact of CDSSs. 9,12–14 To address this issue, we conducted a systematic review to rigorously evaluate the impact of CDSSs linked to EHRs on critical outcomes—mortality, morbidity, and costs—and adopted a narrow definition of the intervention to facilitate its coherent and accurate evaluation. Definitions of Computerized Decision Support Systems (CDSSs) Adopted by Authors of Other Systematic Reviews Bates et al. 15(p524) (and later adopted by Ash et al.^4(p980)) defined a CDSS as a computer-based system providing “passive and active referential information as well as reminders, alerts, and guidelines.” Kawamoto et al. 16(p1) (and later adopted by Bright et al.^9(p29)) identified a CDSS as “any electronic system designed to aid directly in clinical decision making, in which characteristics of individual patients are used to generate patient-specific assessments or recommendations that are then presented to clinicians for consideration.” Payne 17(p47S) classified CDSSs as “computer applications designed to aid clinicians in making diagnostic and therapeutic decisions in patient care.” Open in a separate window