Hospital-Based Physicians' Intubation Decisions and Associated Mental Models when Managing a Critically and Terminally Ill Older Patient. (April 2018)

• Record Type: Journal Article
• Authors: Haliko, Shannon; Downs, Julie; Mohan, Deepika; Arnold, Robert; Barnato, Amber E.
• Is Part Of: Medical decision making. Volume 38:Number 3(2018)
• Page Start: 344
• Page End: 354
• Publication Date: 2018-04
• Subjects: advance directives -- critical care -- end-of-life -- hospital -- intubation -- mechanical ventilation -- mental model -- patient-physician communication -- patient preferences -- shared decision making -- simulation -- terminal care; Medical policy -- Periodicals; Clinical medicine -- Decision making -- Periodicals; Medicine -- Periodicals; Médecine clinique -- Prise de décision -- Périodiques; 362.1
• DOI: 10.1177/0272989X17738958
• Languages: English
• ISSNs: 0272-989X

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.