Sensitivity for multimorbidity: The role of diagnostic uncertainty of physicians when evaluating multimorbid video case-based vignettes

BackgroundMultimorbidity can be defined as the co-occurrence of two or more chronic medical conditions in one person. Within the diagnostic process, accurately detecting a multimorbid disease pattern still poses a major challenge for most physicians, and is known as a source of diagnostic uncertainty.ObjectiveWe investigated, how sensitive, confident, and accurate physicians are in diagnosing multimorbid versus monomorbid patients.MethodsWe created eight video case-based vignettes, which differed in type of morbidity (multimorbid versus monomorbid), field of medical specialization (somatic versus mental), and relatedness of underlying diseases (causally related versus unrelated). In total, 74 physicians (GPs, residents in an emergency department and psychiatrists) watched three to five randomly allocated video cases and had to generate suspected diagnoses at the end of each of three video sequences. Additionally, participating physicians rated subjective confidence for all mentioned diagnoses and for three sequences per case with the help of confidence profiles.ResultsAltogether, physicians made a large number of accurate diagnoses (69%). Nevertheless, the overall number of underdiagnosed multimorbid cases (misses) was significantly higher (71%) than over-diagnosed monomorbid cases (false alarms) (7%).DiscussionAccording to Signal Detection Theory, GPs and psychiatrists both showed lower detection performance for medical cases that lay beyond their own field of specialization. Remarkably, residents show the highest sensitivity for multimorbid cases with an approximately identically detection performance d' slightly over 1 for both field of medical specialization (somatic and mental). Furthermore, higher uncertainty in diagnosing multimorbid cases is related to lower confidence especially at the beginning of a diagnostic process, as well as to unrelated and therefore probably rare disease pattern. Several limitations of the study and the video case-based vignettes are described within the discussion section.ConclusionsPhysicians have to be sensitized for multimorbidity even more, and have to be taught in the prevalence of existing disease combinations. Communicating uncertainty with other specialists could be helpful when faced with a sometimes “fuzzy” pattern of symptoms.背景：共病（Multimorbidity）可定义为单一个体同时罹患两种及以上慢性疾病的状态。在临床诊断流程中，精准识别共病疾病模式仍是多数医师面临的重大挑战，该问题亦被视作诊断不确定性的重要来源。 研究目的：本研究旨在探究医师在诊断共病患者与单病患者时的敏感性、主观信心水平与诊断准确性。 研究方法：我们构建了8个基于视频病例的情景模拟案例（vignettes），这些案例在共病类型（共病vs单病）、医学专科领域（躯体专科vs精神专科）以及基础疾病的相关性（因果相关vs无关联）三个维度存在差异。总计74名医师，包括全科医师（General Practitioners, GPs）、急诊科住院医师及精神科医师，参与本次研究。所有参与者需观看3至5个随机分配的视频病例，并在每个视频序列的末尾提交疑似诊断。此外，参与医师需对所有提及的诊断进行主观信心评分，并借助信心概况表为每个病例的3个序列完成信心评级。 研究结果：整体而言，医师作出的准确诊断占比达69%。然而，未被检出的共病病例（漏诊）总数（71%）显著高于被过度诊断的单病病例（假阳性警报）总数（7%）。 讨论：根据信号检测论（Signal Detection Theory），全科医师与精神科医师在处理超出自身专科领域的临床病例时，检出表现均有所下降。值得注意的是，急诊科住院医师对共病病例的敏感性最高，其在躯体与精神两个专科领域的检出性能指标d'均略高于1且大致相当。此外，共病诊断中的更高不确定性与更低的主观信心相关，尤其在诊断流程初期，同时也与无关联（因而大概率较为罕见）的疾病模式有关。本研究及视频病例情景模拟案例存在若干局限性，相关内容已在讨论章节中详述。 结论：需进一步强化医师对共病的认知，并开展现有疾病组合患病率相关的培训。当面对有时呈现“模糊”特征的症状模式时，与其他专科医师沟通诊断不确定性或将有所助益。