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How Physicians Manage Medical Uncertainty: A Qualitative Study and Conceptual Taxonomy

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  • Paul K. J. Han

    (Center for Outcomes Research and Evaluation, Maine Medical Center, Portland, ME, USA
    Tufts University School of Medicine, Boston, MA, USA)

  • Tania D. Strout

    (Tufts University School of Medicine, Boston, MA, USA
    Department of Emergency Medicine, Maine Medical Center, Portland, ME, USA)

  • Caitlin Gutheil

    (Center for Outcomes Research and Evaluation, Maine Medical Center, Portland, ME, USA
    Tufts University School of Medicine, Boston, MA, USA)

  • Carl Germann

    (Tufts University School of Medicine, Boston, MA, USA
    Department of Emergency Medicine, Maine Medical Center, Portland, ME, USA)

  • Brian King

    (Tufts University School of Medicine, Boston, MA, USA
    Department of Medicine, Maine Medical Center, Portland, ME, USA)

  • Eirik Ofstad

    (Department of Medicine, Nordland Hospital Trust, Bodø, Norway
    Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway)

  • PÃ¥l Gulbrandsen

    (Institute of Clinical Medicine, University of Oslo, Oslo, Norway
    HØKH Research Center, Akershus University Hospital, Lørenskog, Norway)

  • Robert Trowbridge

    (Tufts University School of Medicine, Boston, MA, USA
    Department of Medicine, Maine Medical Center, Portland, ME, USA)

Abstract

Background Medical uncertainty is a pervasive and important problem, but the strategies physicians use to manage it have not been systematically described. Objectives To explore the uncertainty management strategies employed by physicians practicing in acute-care hospital settings and to organize these strategies within a conceptual taxonomy that can guide further efforts to understand and improve physicians’ tolerance of medical uncertainty. Design Qualitative study using individual in-depth interviews. Participants Convenience sample of 22 physicians and trainees (11 attending physicians, 7 residents [postgraduate years 1–3), 4 fourth-year medical students), working within 3 medical specialties (emergency medicine, internal medicine, internal medicine–pediatrics), at a single large US teaching hospital. Measurements Semistructured interviews explored participants’ strategies for managing medical uncertainty and temporal changes in their uncertainty tolerance. Inductive qualitative analysis of audio-recorded interview transcripts was conducted to identify and categorize key themes and to develop a coherent conceptual taxonomy of uncertainty management strategies. Results Participants identified various uncertainty management strategies that differed in their primary focus: 1) ignorance-focused, 2) uncertainty-focused, 3) response-focused, and 4) relationship-focused. Ignorance- and uncertainty-focused strategies were primarily curative (aimed at reducing uncertainty), while response- and relationship-focused strategies were primarily palliative (aimed at ameliorating aversive effects of uncertainty). Several participants described a temporal evolution in their tolerance of uncertainty, which coincided with the development of greater epistemic maturity, humility, flexibility, and openness. Conclusions Physicians and physician-trainees employ a variety of uncertainty management strategies focused on different goals, and their tolerance of uncertainty evolves with the development of several key capacities. More work is needed to understand and improve the management of medical uncertainty by physicians, and a conceptual taxonomy can provide a useful organizing framework for this work.

Suggested Citation

  • Paul K. J. Han & Tania D. Strout & Caitlin Gutheil & Carl Germann & Brian King & Eirik Ofstad & PÃ¥l Gulbrandsen & Robert Trowbridge, 2021. "How Physicians Manage Medical Uncertainty: A Qualitative Study and Conceptual Taxonomy," Medical Decision Making, , vol. 41(3), pages 275-291, April.
  • Handle: RePEc:sae:medema:v:41:y:2021:i:3:p:275-291
    DOI: 10.1177/0272989X21992340
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    References listed on IDEAS

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    1. Hillen, Marij A. & Gutheil, Caitlin M. & Strout, Tania D. & Smets, Ellen M.A. & Han, Paul K.J., 2017. "Tolerance of uncertainty: Conceptual analysis, integrative model, and implications for healthcare," Social Science & Medicine, Elsevier, vol. 180(C), pages 62-75.
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    1. Andreas D. Meid & Lucas Wirbka, 2022. "Can Machine Learning from Real-World Data Support Drug Treatment Decisions? A Prediction Modeling Case for Direct Oral Anticoagulants," Medical Decision Making, , vol. 42(5), pages 587-598, July.

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