Sunnybrook Health Sciences Centre and University of Toronto, Toronto, ON, Canada.
Bioethics. 2011 Jul;25(6):320-5. doi: 10.1111/j.1467-8519.2009.01783.x. Epub 2009 Nov 30.
Ethical challenges that arise within healthcare delivery institutions are currently categorized as either clinical or organizational, based on the type of issue. Despite this common binary issue-based methodology, empirical study and increasing academic dialogue indicate that a clear line cannot easily be drawn between organizational and clinical ethics. Disagreement around end-of-life treatments, for example, often spawn value differences amongst parties at both organizational and clinical levels and requires a resolution to address both the case at hand and large-scale underlying system-level confounders. I refer to issues that contain elements of both clinical and organizational issues as hybrids and propose a new taxonomy to characterize hybrid cases. I contend that salient contextual features of an ethical issue, such as where it is identified, who it impacts and where it is ideally resolved in relation to its scope of impact, should inform procedure. Implementation of a Hybrid taxonomy viewing ethical issues as existing on a continuum furthers that end. The primary goals are to 1) systematize thinking about ethical issues that arise within healthcare delivery institutions and 2) allow the content of the ethical challenge to drive the process, rather than continuing to rely on the traditional binary issue-based choice. Failure to capture the complexity of hybrid situations perpetuates incomplete information and ultimately an inchoate resolution that creates more questions than answers.
目前,基于问题的类型,医疗机构中出现的伦理挑战被分为临床或组织伦理挑战。尽管这种常见的基于二分法的问题方法得到了广泛应用,但实证研究和日益增多的学术对话表明,组织伦理和临床伦理之间很难划出明确的界限。例如,在临终治疗方面的争议往往会在组织和临床层面的各方之间产生价值观的差异,需要解决手头的病例和深层次的系统性混杂因素。我将同时包含临床和组织问题元素的问题称为混合问题,并提出了一种新的分类法来描述混合病例。我认为,一个伦理问题的突出背景特征,如问题的发现地点、受影响的人员以及问题在与其影响范围相关的理想解决地点,都应该为处理程序提供信息。将伦理问题视为连续存在的混合分类法的实施进一步推动了这一目标的实现。主要目标是 1)使医疗机构中出现的伦理问题的思考系统化,2)让伦理挑战的内容来驱动处理过程,而不是继续依赖传统的基于二分法问题的选择。未能捕捉混合情况的复杂性会导致信息不完整,最终导致不明确的解决方案,从而产生更多的问题而不是答案。