Department of Psychiatry, Hôpital Saint-Antoine, Sorbonne Université, AP-HP, Paris, France.
Sorbonne Université, Hôpital de la Pitié Salpêtrière, iCRIN (Infrastructure for Clinical Research In Neurosciences), Brain Institute (ICM), INSERM, CNRS, Paris, France.
Dialogues Clin Neurosci. 2022 Jun 1;23(1):52-61. doi: 10.1080/19585969.2022.2042165. eCollection 2021.
High stake clinical choices in psychiatry can be impacted by external irrelevant factors. A strong understanding of the cognitive and behavioural mechanisms involved in clinical reasoning and decision-making is fundamental in improving healthcare quality. Indeed, the decision in clinical practice can be influenced by errors or approximations which can affect the diagnosis and, by extension, the prognosis: human factors are responsible for a significant proportion of medical errors, often of cognitive origin. Both patient's and clinician's cognitive biases can affect decision-making procedures at different time points. From the patient's point of view, the quality of explicit symptoms and data reported to the psychiatrist might be affected by cognitive biases affecting attention, perception or memory. From the clinician's point of view, a variety of reasoning and decision-making pitfalls might affect the interpretation of information provided by the patient. As personal technology becomes increasingly embedded in human lives, a new concept called digital phenotyping is based on the idea of collecting real-time markers of human behaviour in order to determine the 'digital signature of a pathology'. Indeed, this strategy relies on the assumption that behaviours are 'quantifiable' from data extracted and analysed through connected tools (smartphone, digital sensors and wearable devices) to deduce an 'e-semiology'. In this article, we postulate that implementing digital phenotyping could improve clinical reasoning and decision-making outcomes by mitigating the influence of patient's and practitioner's individual cognitive biases.
精神病学中的高风险临床决策可能受到外部无关因素的影响。深入了解临床推理和决策过程中涉及的认知和行为机制对于提高医疗质量至关重要。事实上,临床实践中的决策可能受到错误或近似值的影响,这些错误或近似值可能会影响诊断,进而影响预后:人为因素是导致医疗差错的主要原因,其中很多差错都源于认知方面的原因。患者和临床医生的认知偏差都会在不同的时间点影响决策过程。从患者的角度来看,向精神科医生报告的明确症状和数据的质量可能会受到影响注意力、感知或记忆的认知偏差的影响。从临床医生的角度来看,各种推理和决策陷阱可能会影响对患者提供的信息的解释。随着个人技术越来越深入地融入人类生活,一种称为数字表型的新概念基于收集人类行为实时标志物的想法,以确定“病理学的数字特征”。事实上,这种策略基于这样的假设,即行为可以通过连接工具(智能手机、数字传感器和可穿戴设备)提取和分析的数据“量化”,从而推断出“电子表型学”。在本文中,我们假设通过减轻患者和从业者个体认知偏差的影响,实施数字表型可以改善临床推理和决策结果。