Patient values and preferences in pulmonary embolism testing in the emergency department
Bibliographic record
Abstract
INTRODUCTION: Patient-centered care is concordant with patient values and preferences. There is a lack of research on patient values and preferences for pulmonary embolism (PE) testing in the emergency department (ED), and a poor physician understanding of patient-specific goals. Our aim was to map patient-specific values, preferences, and expectations regarding PE testing in the ED. METHOD: This qualitative study used constructivist grounded theory to identify patient values and expectations around PE testing in the ED. We conducted semi-structured interviews with ED patients who were being tested for PE in two EDs. Patients who were waiting for PE imaging or D-dimer results were approached and consented to take part in a 30-minute audio-recorded interview. Each interview was transcribed verbatim and analyzed using constant comparative coding. The interview script was modified to maximize information on emerging themes. Major themes and subthemes were derived, each representing an opportunity, barrier, or value to address with patient-centered PE testing. RESULTS: From 30 patient interviews, we mapped four major themes: patient satisfaction comes from addressing the patient's primary concern (for example, their pain); patients expect individualized care; patients prefer imaging over clinical examination for PE testing; and patients expect 100% confidence from their emergency physician when given a diagnosis. Subthemes included symptomatic relief, finding a diagnosis, receiving tests, rapid progression through their care, perception of highly accurate CT scans, willingness to seek a second opinion, direct physician communication, and expectation of case-specific testing with cognitive reassurance. CONCLUSION: Addressing each of these four themes by realigning ED processes could provide patient-centered PE testing.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".