Article Data

  • Views 1425
  • Dowloads 185

Original Research

Open Access Special Issue

Effects of the quality of medical history taking on diagnostic accuracy

  • Stefan Götz1
  • Julie Fournier1
  • Kai Tisjlar2
  • Timur Sellmann3,4
  • Stephan Marsch2,*,

1University of Basel, 4031 Basel, Switzerland

2Intensive Care, University Hospital Basel, 4031 Basel, Switzerland

3Department of Anaesthesiology and Intensive Care Medicine, Bethesda Hospital, 47053 Duisburg, Germany

4University of Witten/Herdecke, 58455 Witten, Germany

DOI: 10.22514/sv.2023.081 Vol.19,Issue 5,September 2023 pp.68-74

Submitted: 29 December 2022 Accepted: 14 March 2023

Published: 08 September 2023

(This article belongs to the Special Issue Medical Simulation - success in education, future of science)

*Corresponding Author(s): Stephan Marsch E-mail:


Diagnostic errors are a relevant health-care problem. Although medical history taking is usually the first step in patients’ assessment there are only limited data on the association of its quality and diagnostic accuracy. Accordingly, this prospective randomized simulator-based single-blind trial aimed to investigate the effects of initial cues and history taking skills on diagnostic accuracy. 198 medical students (135 females) were given the task to assess a patient presenting with simulated acute pulmonary embolism. Participants were randomized to six versions of the scenario differing only in the initial cues, i.e., in the reply of the patient to the initial question about the reason for his visit. In three of six versions, initial cues were restricted to thoracic symptoms (chest pain, dyspnoea, or combination of both). In the remaining three versions, initial cues consisted of thoracic and extra-thoracic (leg pain, immobilization) symptoms. The primary outcome was diagnostic accuracy. The number of initial cues was unrelated to diagnostic accuracy. However, the combination of extra-thoracic and thoracic cues resulted in a higher diagnostic accuracy than thoracic cues only (52/96 vs. 35/102, p = 0.006). In multivariate regression, the number of questions asked from the categories “risk factors of pulmonary embolism” (regression coefficient 0.15, p < 0.001) and “dyspnea” (regression coefficient 0.12, p < 0.001) predicted diagnostic accuracy. Moreover, questions relating to “immobilization” (regression coefficient 0.42, p < 0.001), “onset of dyspnea” (regression coefficient 0.23, p = 0.003), and “modifying factors of chest pain” (regression coefficient 0.20, p = 0.04) independently predicted diagnostic accuracy. Interestingly, more systematic history taking was associated with lower diagnostic accuracy (regression coefficient −0.27, p < 0.001). The present trial demonstrates that during history taking cues initially revealed by the patient, kind and category of questions asked during the interview, and the interview’s structural systematics affect diagnostic accuracy.


Randomized trial; Medical simulation; Diagnostic error; Initial cue; Emergency medicine; Medical education

Cite and Share

Stefan Götz,Julie Fournier,Kai Tisjlar,Timur Sellmann,Stephan Marsch. Effects of the quality of medical history taking on diagnostic accuracy. Signa Vitae. 2023. 19(5);68-74.


[1] Institute of Medicine and National Academies of Sciences, Engineering and Medicine. Improving diagnosis in health care. The National Academies Press: Washington DC. 2015.

[2] Newman-Toker DE, Wang Z, Zhu Y, Nassery N, Saber Tehrani AS, Schaffer AC, et al. Rate of diagnostic errors and serious misdiagnosis-related harms for major vascular events, infections, and cancers: toward a national incidence estimate using the “Big Three”. Diagnosis. 2021; 8: 67–84.

[3] Hertwig R, Meier N, Nickel C, Zimmermann P, Ackermann S, Woike JK, et al. Correlates of diagnostic accuracy in patients with nonspecific complaints. Medical Decision Making. 2013; 33: 533–543.

[4] Solmi M, Fiedorowicz J, Poddighe L, Delogu M, Miola A, Høye A, et al. Disparities in screening and treatment of cardiovascular diseases in patients with mental disorders across the world: systematic review and meta-analysis of 47 observational studies. American Journal of Psychiatry. 2021; 178: 793–803.

[5] Meyer FML, Filipovic MG, Balestra GM, Tisljar K, Sellmann T, Marsch S. Diagnostic errors induced by a wrong a priori diagnosis: a prospective randomized simulator-based trial. Journal of Clinical Medicine. 2021; 10: 826–839.

[6] Setrakian J, Gauthier Gv, Bergeron L, Chamberland M, St-Onge C. Comparison of assessment by a virtual patient and by clinician-educators of medical students’ history-taking skills: exploratory descriptive study. JMIR Medical Education. 2020; 6: e14428.

[7] Hautz WE, Kämmer JE, Hautz SC, Sauter TC, Zwaan L, Exadaktylos AK, et al. Diagnostic error increases mortality and length of hospital stay in patients presenting through the emergency room. Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine. 2019; 27: 54.

[8] Kunitomo K, Harada T, Watari T. Cognitive biases encountered by physicians in the emergency room. BMC Emergency Medicine. 2022; 22: 148–155.

[9] Hendriksen JMT, Koster-van Ree M, Morgenstern MJ, Oudega R, Schutgens REG, Moons KGM, et al. Clinical characteristics associated with diagnostic delay of pulmonary embolism in primary care: a retrospective observational study. BMJ Open. 2017; 7: e012789.

[10] Mansella G, Keil C, Nickel CH, Eken C, Wirth C, Tzankov A, et al. Delayed diagnosis in pulmonary embolism: frequency, patient characteristics, and outcome. Respiration. 2020; 99: 589–597.

[11] Swan D, Hitchen S, Klok FA, Thachil J. The problem of under-diagnosis and over-diagnosis of pulmonary embolism. Thrombosis Research. 2019; 177: 122–129.

[12] van Maanen R, Trinks-Roerdink EM, Rutten FH, Geersing GJ. A systematic review and meta-analysis of diagnostic delay in pulmonary embolism. European Journal of General Practice. 2022; 28: 165–172.

[13] Cheng A, Kessler D, Mackinnon R, Chang TP, Nadkarni VM, Hunt EA, et al. Reporting guidelines for health care simulation research. Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare. 2016; 11: 238–248.

[14] Le Gal G, Righini M, Roy P, Sanchez O, Aujesky D, Bounameaux H, et al. Prediction of pulmonary embolism in the emergency department: the revised geneva score. Annals of Internal Medicine. 2006; 144: 165.

[15] Anderson D, Rodger M, Ginsberg J, Kearon C, Gent M, Turpie A, et al. Derivation of a simple clinical model to categorize patients probability of pulmonary embolism: increasing the models utility with the SimpliRED D-dimer. Thrombosis and Haemostasis. 2000; 83: 416–420.

[16] van der Hulle T, Cheung WY, Kooij S, Beenen LFM, van Bemmel T, van Es J, et al. Simplified diagnostic management of suspected pulmonary embolism (the YEARS study): a prospective, multicentre, cohort study. The Lancet. 2017; 390: 289–297.

[17] Wigton RS, Hoellerich VL, Patil KD. How physicians use clinical information in diagnosing pulmonary embolism. Medical Decision Making. 1986; 6: 2–11.

[18] Smith SB, Geske JB, Morgenthaler TI. Risk factors associated with delayed diagnosis of acute pulmonary embolism. The Journal of Emergency Medicine. 2012; 42: 1–6.

[19] Delzell JE, Chumley H, Webb R, Chakrabarti S, Relan A. Information-gathering patterns associated with higher rates of diagnostic error. Advances in Health Sciences Education. 2009; 14: 697.

[20] Sutton R, van Dijk N, Wieling W. Clinical history in management of suspected syncope: a powerful diagnostic tool. Cardiology Journal. 2014; 21: 651–657.

[21] Alcazar Artero PM, Pardo Rios M, Greif R, Ocampo Cervantes AB, Gijon-Nogueron G, Barcala-Furelos R, et al. Efficiency of virtual reality for cardiopulmonary resuscitation training of adult laypersons: a systematic review. Medicine. 2023; 102: e32736.

[22] Zackoff MW, Cruse B, Sahay RD, Fei L, Saupe J, Schwartz J, et al. Development and implementation of augmented reality enhanced high-fidelity simulation for recognition of patient decompensation. Simulation in Healthcare: The Journal of the Society for Simulation in Healthcare. 2021; 16: 221–230.

[23] Zwaan L, Monteiro S, Sherbino J, Ilgen J, Howey B, Norman G. Is bias in the eye of the beholder? A vignette study to assess recognition of cognitive biases in clinical case workups. BMJ Quality & Safety. 2017; 26: 104–110.

Abstracted / indexed in

Science Citation Index Expanded (SciSearch) Created as SCI in 1964, Science Citation Index Expanded now indexes over 9,200 of the world’s most impactful journals across 178 scientific disciplines. More than 53 million records and 1.18 billion cited references date back from 1900 to present.

Journal Citation Reports/Science Edition Journal Citation Reports/Science Edition aims to evaluate a journal’s value from multiple perspectives including the journal impact factor, descriptive data about a journal’s open access content as well as contributing authors, and provide readers a transparent and publisher-neutral data & statistics information about the journal.

Chemical Abstracts Service Source Index The CAS Source Index (CASSI) Search Tool is an online resource that can quickly identify or confirm journal titles and abbreviations for publications indexed by CAS since 1907, including serial and non-serial scientific and technical publications.

Index Copernicus The Index Copernicus International (ICI) Journals database’s is an international indexation database of scientific journals. It covered international scientific journals which divided into general information, contents of individual issues, detailed bibliography (references) sections for every publication, as well as full texts of publications in the form of attached files (optional). For now, there are more than 58,000 scientific journals registered at ICI.

Geneva Foundation for Medical Education and Research The Geneva Foundation for Medical Education and Research (GFMER) is a non-profit organization established in 2002 and it works in close collaboration with the World Health Organization (WHO). The overall objectives of the Foundation are to promote and develop health education and research programs.

Scopus: CiteScore 1.0 (2022) Scopus is Elsevier's abstract and citation database launched in 2004. Scopus covers nearly 36,377 titles (22,794 active titles and 13,583 Inactive titles) from approximately 11,678 publishers, of which 34,346 are peer-reviewed journals in top-level subject fields: life sciences, social sciences, physical sciences and health sciences.

Embase Embase (often styled EMBASE for Excerpta Medica dataBASE), produced by Elsevier, is a biomedical and pharmacological database of published literature designed to support information managers and pharmacovigilance in complying with the regulatory requirements of a licensed drug.

Submission Turnaround Time