‘This time is different’: physician knowledge in the age of artificial intelligence

IF 5.6 1区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Gurpreet Dhaliwal
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Abstract

Great diagnosticians are often portrayed as recognising rare diseases that evade the efforts of mere mortals. This makes for great TV and local legends, but does not reflect daily practice, where the most common diagnostic challenge is discriminating between common conditions like pneumonia and heart failure or appendicitis and gastroenteritis. Questions about how to train the brain to make those distinctions are central to the efforts of many clinician educators. An unresolved issue is whether the structure of knowledge (about diseases and diagnostic pathways) in the physician’s long-term memory or the clinician’s mode of cognition (intuitive or analytical thinking) is more deterministic of diagnostic success. A study1 in this issue of BMJQS sheds light on this issue, but also invites a broader question: is physician cognition still essential for this task at all? In a two-phase experiment, Mamede et al 1 asked 68 internal medicine residents to recall from memory the key clinical features of six conditions (vitamin B12 deficiency, inflammatory bowel disease, hyperthyroidism, adrenal insufficiency, appendicitis, endocarditis). Physicians were categorised as high knowledge (HK) or low knowledge (LK) based on their recall of discriminating features, which are essential to differentiate one condition from common competing diagnoses. One week later, the residents were given related clinical vignettes and asked to render a diagnosis. Half of the vignettes had a salient distracting feature (SDF), a clinical finding that may prompt the physician to suspect a condition other than the correct diagnosis. For example, a vignette of a confused patient included a family history of dementia, which was irrelevant in the face of strong evidence for vitamin B12 deficiency. The authors used the SDF as a model for activating the anchoring heuristic , which is a tendency to adhere to an early judgement triggered by a data point. Essentially, …
这次不一样":人工智能时代的医生知识
伟大的诊断师常常被描绘成能识别出罕见疾病的人,而普通人却无能为力。这在电视上和地方传说中很有说服力,但并不反映日常实践,在日常实践中,最常见的诊断挑战是区分肺炎和心力衰竭或阑尾炎和肠胃炎等常见疾病。如何训练大脑做出这些区分是许多临床医生教育工作者努力的核心问题。一个悬而未决的问题是,是医生长期记忆中的知识结构(关于疾病和诊断途径)还是临床医生的认知模式(直觉思维还是分析思维)更能决定诊断的成功与否。本期《BMJQS》上的一项研究1 揭示了这一问题,但同时也引出了一个更广泛的问题:医生的认知对于这项任务是否仍然至关重要?在一项分两个阶段进行的实验中,Mamede 等人1 要求 68 名内科住院医生凭记忆回忆六种疾病(维生素 B12 缺乏症、炎症性肠病、甲状腺功能亢进、肾上腺功能不全、阑尾炎、心内膜炎)的主要临床特征。根据医生对鉴别特征的回忆,他们被分为高知识水平(HK)和低知识水平(LK)。一周后,给住院医生提供相关的临床案例,要求他们做出诊断。有一半的小故事具有突出的干扰特征(SDF),这种临床发现可能会促使医生怀疑某种疾病而不是正确的诊断。例如,一位神志不清的病人的小故事中有痴呆症家族史,而这与维生素 B12 缺乏症的有力证据无关。作者将 SDF 作为激活锚定启发式的模型,锚定启发式是一种坚持由数据点引发的早期判断的倾向。从本质上讲,...
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来源期刊
BMJ Quality & Safety
BMJ Quality & Safety HEALTH CARE SCIENCES & SERVICES-
CiteScore
9.80
自引率
7.40%
发文量
104
审稿时长
4-8 weeks
期刊介绍: BMJ Quality & Safety (previously Quality & Safety in Health Care) is an international peer review publication providing research, opinions, debates and reviews for academics, clinicians and healthcare managers focused on the quality and safety of health care and the science of improvement. The journal receives approximately 1000 manuscripts a year and has an acceptance rate for original research of 12%. Time from submission to first decision averages 22 days and accepted articles are typically published online within 20 days. Its current impact factor is 3.281.
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