IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0215049.html
   My bibliography  Save this article

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

Author

Listed:
  • Daniel Hausmann
  • Vera Kiesel
  • Lukas Zimmerli
  • Narcisa Schlatter
  • Amandine von Gunten
  • Nadine Wattinger
  • Thomas Rosemann

Abstract

Background: Multimorbidity 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. Objective: We investigated, how sensitive, confident, and accurate physicians are in diagnosing multimorbid versus monomorbid patients. Methods: We 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. Results: Altogether, 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%). Discussion: According 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. Conclusions: Physicians 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.

Suggested Citation

  • Daniel Hausmann & Vera Kiesel & Lukas Zimmerli & Narcisa Schlatter & Amandine von Gunten & Nadine Wattinger & Thomas Rosemann, 2019. "Sensitivity for multimorbidity: The role of diagnostic uncertainty of physicians when evaluating multimorbid video case-based vignettes," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-16, April.
    • Handle: RePEc:plo:pone00:0215049
    DOI: 10.1371/journal.pone.0215049
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0215049
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0215049&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0215049?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. repec:cup:judgdm:v:3:y:2008:i::p:229-243 is not listed on IDEAS
    2. Karen E. Lutfey & Carol L. Link & Lisa D. Marceau & Richard W. Grant & Ann Adams & Sara Arber & Johannes Siegrist & Markus Bönte & Olaf von dem Knesebeck & John B. McKinlay, 2009. "Diagnostic Certainty as a Source of Medical Practice Variation in Coronary Heart Disease: Results from a Cross-National Experiment of Clinical Decision Making," Medical Decision Making, , vol. 29(5), pages 606-618, September.
    3. Michael Siegrist & Timothy C. Earle & Heinz Gutscher, 2003. "Test of a Trust and Confidence Model in the Applied Context of Electromagnetic Field (EMF) Risks," Risk Analysis, John Wiley & Sons, vol. 23(4), pages 705-716, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haywantee Ramkissoon, 2021. "Social Bonding and Public Trust/Distrust in COVID-19 Vaccines," Sustainability, MDPI, vol. 13(18), pages 1-6, September.
    2. Nahui Zhen & Jon Barnett & Michael Webber, 2020. "Is Trust Always a Precondition for Effective Water Resource Management?," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(4), pages 1423-1436, March.
    3. Kazuya Nakayachi & George Cvetkovich, 2010. "Public Trust in Government Concerning Tobacco Control in Japan," Risk Analysis, John Wiley & Sons, vol. 30(1), pages 143-152, January.
    4. Gianluca Stefani & Alessio Cavicchi & Donato Romano & Alexandra E. Lobb, 2008. "Determinants of intention to purchase chicken in Italy: the role of consumer risk perception and trust in different information sources," Agribusiness, John Wiley & Sons, Ltd., vol. 24(4), pages 523-537.
    5. William J. Burns & Ellen Peters & Paul Slovic, 2012. "Risk Perception and the Economic Crisis: A Longitudinal Study of the Trajectory of Perceived Risk," Risk Analysis, John Wiley & Sons, vol. 32(4), pages 659-677, April.
    6. Silvia Banfi & Massimo Filippini & Andrea Horehájová, 2007. "Hedonic Price Functions for Zurich and Lugano with Special Focus on Electrosmog," CEPE Working paper series 07-57, CEPE Center for Energy Policy and Economics, ETH Zurich.
    7. Branden B. Johnson & Mathew P. White, 2010. "The Importance of Multiple Performance Criteria for Understanding Trust in Risk Managers," Risk Analysis, John Wiley & Sons, vol. 30(7), pages 1099-1115, July.
    8. Daniela Marchetti & Roberta Maiella & Rocco Palumbo & Melissa D’Ettorre & Irene Ceccato & Marco Colasanti & Adolfo Di Crosta & Pasquale La Malva & Emanuela Bartolini & Daniela Biasone & Nicola Mammare, 2023. "Self-Reported Mental Health and Psychosocial Correlates during the COVID-19 Pandemic: Data from the General Population in Italy," Data, MDPI, vol. 8(6), pages 1-7, June.
    9. Michael Siegrist & Philipp Hübner & Christina Hartmann, 2018. "Risk Prioritization in the Food Domain Using Deliberative and Survey Methods: Differences between Experts and Laypeople," Risk Analysis, John Wiley & Sons, vol. 38(3), pages 504-524, March.
    10. Tianjun Feng & L. Robin Keller & Ping Wu & Yifan Xu, 2014. "An Empirical Study of the Toxic Capsule Crisis in China: Risk Perceptions and Behavioral Responses," Risk Analysis, John Wiley & Sons, vol. 34(4), pages 698-710, April.
    11. Peng Liu & Run Yang & Zhigang Xu, 2019. "Public Acceptance of Fully Automated Driving: Effects of Social Trust and Risk/Benefit Perceptions," Risk Analysis, John Wiley & Sons, vol. 39(2), pages 326-341, February.
    12. Jamison, Amelia M. & Quinn, Sandra Crouse & Freimuth, Vicki S., 2019. "“You don't trust a government vaccine”: Narratives of institutional trust and influenza vaccination among African American and white adults," Social Science & Medicine, Elsevier, vol. 221(C), pages 87-94.
    13. Michael Siegrist, 2010. "Trust and Confidence: The Difficulties in Distinguishing the Two Concepts in Research," Risk Analysis, John Wiley & Sons, vol. 30(7), pages 1022-1024, July.
    14. Mathew P. White & Branden B. Johnson, 2010. "The Intuitive Detection Theorist (IDT) Model of Trust in Hazard Managers," Risk Analysis, John Wiley & Sons, vol. 30(8), pages 1196-1209, August.
    15. Marie‐Eve Cousin & Michael Siegrist, 2011. "Cell Phones and Health Concerns: Impact of Knowledge and Voluntary Precautionary Recommendations," Risk Analysis, John Wiley & Sons, vol. 31(2), pages 301-311, February.
    16. Nik Thompson & Tanya McGill & Anna Bunn & Rukshan Alexander, 2020. "Cultural factors and the role of privacy concerns in acceptance of government surveillance," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(9), pages 1129-1142, September.
    17. Ye, Maoxin & Lyu, Zeyu, 2020. "Trust, risk perception, and COVID-19 infections: Evidence from multilevel analyses of combined original dataset in China," Social Science & Medicine, Elsevier, vol. 265(C).
    18. Silvia Banfi & Massimo Filippini & Andrea Horehájová, 2008. "Valuation of Environmental Goods in Profit and Non-Profit Housing Sectors: Evidence from the Rental Market in the City of Zurich," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 144(IV), pages 631-654, December.
    19. Branden B. Johnson & William K. Hallman & Cara L. Cuite, 2015. "Modeling Retrospective Attribution of Responsibility to Hazard‐Managing Institutions: An Example Involving a Food Contamination Incident," Risk Analysis, John Wiley & Sons, vol. 35(3), pages 423-433, March.
    20. Ding, Hongxiang & Zhang, Junyi, 2021. "Dynamic associations between temporal behavior changes caused by the COVID-19 pandemic and subjective assessments of policymaking: A case study in Japan," Transport Policy, Elsevier, vol. 110(C), pages 58-70.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0215049. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.