Chorpita Bruce F, Daleiden Eric L, Bernstein Adam D
UCLA Department of Psychology, University of California, Los Angeles, Franz Hall 3227, Los Angeles, CA, 90095, USA.
PracticeWise, LLC, 340 Lee Avenue, Satellite Beach, FL, 32937, USA.
Adm Policy Ment Health. 2016 May;43(3):471-7. doi: 10.1007/s10488-015-0702-5.
We select and comment on concepts and examples from the target articles in this special issue on measurement feedback systems, placing them in the context of some of our own insights and ideas about measurement feedback systems, and where those systems lie at the intersection of technology and decision making. We contend that, connected to the many implementation challenges relevant to many new technologies, there are fundamental design challenges that await a more elaborate specification of the clinical information and decision models that underlie these systems. Candidate features of such models are discussed, which include referencing multiple evidence bases, facilitating observed and expected value comparisons, fostering collaboration, and allowing translation across multiple ontological systems. We call for a new metaphor for these technologies that goes beyond measurement feedback and encourages a deeper consideration of the increasingly complex clinical decision models needed to manage the uncertainty of delivering clinical care.
我们从本期关于测量反馈系统的特刊中的目标文章中选取并评论了一些概念和示例，将它们置于我们自己对测量反馈系统的一些见解和想法的背景下，以及这些系统处于技术与决策交叉点的背景中。我们认为，与许多新技术相关的众多实施挑战相联系的是，存在一些基本的设计挑战，这些挑战等待着对作为这些系统基础的临床信息和决策模型进行更详尽的规范。讨论了此类模型的候选特征，其中包括参考多个证据库、便于观察值与期望值的比较、促进协作以及允许在多个本体系统之间进行转换。我们呼吁为这些技术创造一个新的隐喻，它超越测量反馈，并鼓励更深入地思考管理临床护理不确定性所需的日益复杂的临床决策模型。
