Helping Patients Navigate the Emergency Department: Assessing the Utility of a Poster Illustrating the Patient Journey
Bibliographic record
Abstract
Patients often have limited understanding of the emergency department (ED) care process, which can increase anxiety, frustration, and confusion. This study implemented and assessed the usefulness of a poster explaining the ED care process. A large wall-mounted poster illustrating the patient journey was developed; two different data collection techniques were used. First, a QR code/URL was used to passively collect patient reactions to the poster in 15 EDs. Due to limited response, a paper survey was developed and delivered by research assistants in three study sites using a consecutive sampling method. A total of 67 responses were collected from the QR/URL method between October 2017 and July 2021. The in-person survey collected 316 responses, of which approximately half of the respondents were women and the majority identified as white. Half of the respondents presented to the ED alone. Nearly 40% of respondents had noticed and engaged with the poster without prompting. Once prompted, the majority of respondents understood its content and over half found the information to be extremely or very helpful in preparing them for their ED journey. Respondents identified three additional key information needs: 1) real-time waiting times, 2) triaging scoring information, and 3) support on what to do while waiting. Patient journey posters may assist patients in navigating the ED care process. Exploring alternative delivery methods, personalizing materials and addressing wait times may increase usefulness. Reconceptualizing the waiting room as an opportunity for patient education and communication may alleviate patient fears and better prepare them for the ED journey.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".