Managing Multiplicity: Conceptualizing Physician Cognition in Multipatient Environments
Bibliographic record
Abstract
PURPOSE: Emergency physicians (EPs) regularly manage multiple patients simultaneously, often making time-sensitive decisions around priorities for multiple patients. Few studies have explored physician cognition in multipatient scenarios. The authors sought to develop a conceptual framework to describe how EPs think in busy, multipatient environments. METHOD: From July 2014 to May 2015, a qualitative study was conducted at McMaster University, using a think-aloud protocol to examine how 10 attending EPs and 10 junior residents made decisions in multipatient environments. Participants engaged in the think-aloud exercise for five different simulated multipatient scenarios. Transcripts from recorded interviews were analyzed inductively, with an iterative process involving two independent coders, and compared between attendings and residents. RESULTS: The attending EPs and junior residents used similar processes to prioritize patients in these multipatient scenarios. The think-aloud processes demonstrated a similar process used by almost all participants. The cognitive task of patient prioritization consisted of three components: a brief overview of the entire cohort of patients to determine a general strategy; an individual chart review, whereby the participant created a functional patient story from information available in a file (i.e., vitals, brief clinical history); and creation of a relative priority list. Compared with residents, the attendings were better able to construct deeper and more complex patient stories. CONCLUSIONS: The authors propose a conceptual framework for how EPs prioritize care for multiple patients in complex environments. This study may be useful to teachers who train physicians to function more efficiently in busy clinical environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".