IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v38y2018i3p344-354.html
   My bibliography  Save this article

Hospital-Based Physicians’ Intubation Decisions and Associated Mental Models when Managing a Critically and Terminally Ill Older Patient

Author

Listed:
  • Shannon Haliko

    (Department of Critical Care Medicine, Hoag Hospital, Newport Beach, CA, USA)

  • Julie Downs

    (Department of Social and Decision Sciences, Carnegie Mellon University, Pittsburgh, PA, USA)

  • Deepika Mohan

    (Department of Critical Care Medicine and Department of Surgery, University of Pittsburgh, Pittsburgh, PA, USA)

  • Robert Arnold

    (Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA)

  • Amber E. Barnato

    (Dartmouth Institute, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA)

Abstract

Background. Variation in the intensity of acute care treatment at the end of life is influenced more strongly by hospital and provider characteristics than patient preferences. Objective. We sought to describe physicians’ mental models (i.e., thought processes) when encountering a simulated critically and terminally ill older patient, and to compare those models based on whether their treatment plan was patient preference-concordant or preference-discordant. Methods. Seventy-three hospital-based physicians from 3 academic medical centers engaged in a simulated patient encounter and completed a mental model interview while watching the video recording of their encounter. We used an “expert†model to code the interviews. We then used Kruskal–Wallis tests to compare the weighted mental model themes of physicians who provided preference-concordant treatment with those who provided preference-discordant treatment. Results. Sixty-six (90%) physicians provided preference-concordant treatment and 7 (10%) provided preference-discordant treatment (i.e., they intubated the patient). Physicians who intubated the patient were more likely to emphasize the reversible and emergent nature of the patient situation (z = −2.111, P = 0.035), their own comfort (z = −2.764, P = 0.006), and rarely focused on explicit patient preferences (z = 2.380, P = 0.017). Limitations. Post-decisional interviewing with audio/video prompting may induce hindsight bias. The expert model has not yet been validated and may not be exhaustive. The small sample size limits generalizability and power. Conclusions. Hospital-based physicians providing preference-discordant used a different mental model for decision making for a critically and terminally ill simulated case. These differences may offer targets for future interventions to promote preference-concordant care for seriously ill patients.

Suggested Citation

  • Shannon Haliko & Julie Downs & Deepika Mohan & Robert Arnold & Amber E. Barnato, 2018. "Hospital-Based Physicians’ Intubation Decisions and Associated Mental Models when Managing a Critically and Terminally Ill Older Patient," Medical Decision Making, , vol. 38(3), pages 344-354, April.
  • Handle: RePEc:sae:medema:v:38:y:2018:i:3:p:344-354
    DOI: 10.1177/0272989X17738958
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X17738958
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0272989X17738958?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. Matthew D. Wood & Ann Bostrom & Todd Bridges & Igor Linkov, 2012. "Cognitive Mapping Tools: Review and Risk Management Needs," Risk Analysis, John Wiley & Sons, vol. 32(8), pages 1333-1348, 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. Elizabeth L. Petrun Sayers & Christopher A. Craig & Emily Skonicki & Grace Gahlon & Susan Gilbertz & Song Feng, 2021. "Evaluating STEM-Based Sustainability Understanding: A Cognitive Mapping Approach," Sustainability, MDPI, vol. 13(14), pages 1-23, July.
    2. Brown, Jason D. & Ivanova, Viktoria & Mehta, Nisha & Skrodzki, Donna & Gerrits, Julie, 2013. "Social needs of aboriginal foster parents," Children and Youth Services Review, Elsevier, vol. 35(11), pages 1886-1893.
    3. Meredith Frances Dobbie & Rebekah Ruth Brown, 2014. "A Framework for Understanding Risk Perception, Explored from the Perspective of the Water Practitioner," Risk Analysis, John Wiley & Sons, vol. 34(2), pages 294-308, February.
    4. John Hamer Powell & Michael Hammond & Albert Chen & Navonil Mustafee, 2018. "Human Agency in Disaster Planning: A Systems Approach," Risk Analysis, John Wiley & Sons, vol. 38(7), pages 1422-1443, July.
    5. Zhu, Xun & Pasch, Timothy J. & Bergstrom, Aaron, 2020. "Understanding the structure of risk belief systems concerning drone delivery: A network analysis," Technology in Society, Elsevier, vol. 62(C).
    6. Louie Rivers III & Udita Sanga & Amadou Sidibe & Alexa Wood & Rajiv Paudel & Sandra T. Marquart-Pyatt & Arika Ligmann-Zielinska & Laura Schmitt Olabisi & Eric Jing Du & Saweda Liverpool-Tasie, 2018. "Mental models of food security in rural Mali," Environment Systems and Decisions, Springer, vol. 38(1), pages 33-51, March.
    7. Ineke Malsch & Vrishali Subramanian & Elena Semenzin & Alex Zabeo & Danail Hristozov & Martin Mullins & Finbarr Murphy & Igor Linkov & Antonio Marcomini, 2017. "Comparing mental models of prospective users of the sustainable nanotechnology decision support system," Environment Systems and Decisions, Springer, vol. 37(4), pages 465-483, December.
    8. Ayedh Almutairi & John P. Wheeler & David L. Slutzky & James H. Lambert, 2019. "Integrating Stakeholder Mapping and Risk Scenarios to Improve Resilience of Cyber‐Physical‐Social Networks," Risk Analysis, John Wiley & Sons, vol. 39(9), pages 2093-2112, September.
    9. Masayasu Asai & Takashi Hayashi & Mitasu Yamamoto, 2019. "Mental Model Analysis of Biogas Energy Perceptions and Policy Reveals Potential Constraints in a Japanese Farm Community," Sustainability, MDPI, vol. 11(1), pages 1-20, January.
    10. Thomas J. Cova & Philip E. Dennison & Dapeng Li & Frank A. Drews & Laura K. Siebeneck & Michael K. Lindell, 2017. "Warning Triggers in Environmental Hazards: Who Should Be Warned to Do What and When?," Risk Analysis, John Wiley & Sons, vol. 37(4), pages 601-611, April.

    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:sae:medema:v:38:y:2018:i:3:p:344-354. 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: SAGE Publications (email available below). General contact details of provider: .

    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.