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使用主动风险控制生成选项(GO-ARC)技术可带来更稳健的风险控制选项。

Use of the Generating Options for Active Risk Control (GO-ARC) Technique can lead to more robust risk control options.

作者信息

Card Alan J, Simsekler Mecit Can Emre, Clark Michael, Ward James R, Clarkson P John

机构信息

Evidence-Based Health Solutions, LLC, Notre Dame, IN, USA.

Engineering Design Centre, Department of Engineering, University of Cambridge, Cambridge, UK.

出版信息

Int J Risk Saf Med. 2014;26(4):199-211. doi: 10.3233/JRS-140636.

Abstract

BACKGROUND

Risk assessment is widely used to improve patient safety, but healthcare workers are not trained to design robust solutions to the risks they uncover. This leads to an overreliance on the weakest category of risk control recommendations: administrative controls. Increasing the proportion of non-administrative risk control options (NARCOs) generated would enable (though not ensure) the adoption of more robust solutions.

OBJECTIVES

Experimentally assess a method for generating stronger risk controls: The Generating Options for Active Risk Control (GO-ARC) Technique.

METHODS

Participants generated risk control options in response to two patient safety scenarios. Scenario 1 (baseline): All participants used current practice (unstructured brainstorming). Scenario 2: Control group used current practice; intervention group used the GO-ARC Technique. To control for individual differences between participants, analysis focused on the change in the proportion of NARCOs for each group.

CONTROL GROUP

Proportion of NARCOs decreased from 0.18 at baseline to 0.12. Intervention group: Proportion increased from 0.10 at baseline to 0.29 using the GO-ARC Technique. Results were statistically significant. There was no decrease in the number of administrative controls generated by the intervention group.

CONCLUSION

The Generating Options for Active Risk Control (GO-ARC) Technique appears to lead to more robust risk control options.

摘要

背景

风险评估被广泛用于提高患者安全,但医护人员未接受过设计针对所发现风险的可靠解决方案的培训。这导致过度依赖最薄弱的风险控制建议类别:行政控制措施。增加非行政风险控制选项(NARCOs)的生成比例将有助于(尽管不能确保)采用更可靠的解决方案。

目的

通过实验评估一种生成更强有力风险控制措施的方法:主动风险控制生成选项(GO-ARC)技术。

方法

参与者针对两个患者安全场景生成风险控制选项。场景1(基线):所有参与者采用当前做法(无结构化头脑风暴)。场景2:对照组采用当前做法;干预组采用GO-ARC技术。为控制参与者之间的个体差异,分析聚焦于每组NARCOs比例的变化。

对照组

NARCOs比例从基线时的0.18降至0.12。干预组:采用GO-ARC技术后,比例从基线时的0.10增至0.29。结果具有统计学意义。干预组生成的行政控制措施数量没有减少。

结论

主动风险控制生成选项(GO-ARC)技术似乎能带来更可靠的风险控制选项。

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