Shared Decision Making in Patients With Suspected Uncomplicated Ureterolithiasis: A Decision Aid Development Study
Bibliographic record
Abstract
OBJECTIVE: The objective was to develop a decision aid (DA) to facilitate shared decision making (SDM) around whether to obtain computed tomography (CT) imaging in patients presenting to the emergency department (ED) with suspected uncomplicated ureterolithiasis. METHODS: We used evidence-based DA development methods, including qualitative methods and iterative stakeholder engagement, to develop and refine a DA. Guided by the Ottawa Decision Support Framework, International Patient Decision Aid Standards (IPDAS), and a steering committee made up of stakeholders, we conducted interviews and focus groups with a purposive sample of patients, community members, emergency clinicians, and other stakeholders. We used an iterative process to code the transcripts and identify themes. We beta-tested the DA with patient-clinician dyads facing the decision in real time. RESULTS: From August 2018 to August 2019, we engaged 102 participants in the design and iterative refinement of a DA focused on diagnostic options for patients with suspected ureterolithiasis. Forty-six were ED patients, community members, or patients with ureterolithiasis, and the remaining were emergency clinicians (doctors, residents, advanced practitioners), researchers, urologists, nurses, or other physicians. Patients and clinicians identified several key decisional needs including an understanding of accuracy, uncertainty, radiation exposure/cancer risk, and clear return precautions. Patients and community members identified facilitators to SDM, such as a checklist of signs and symptoms. Many stakeholders, including both patients and ED clinicians, expressed a strong pro-CT bias. A six-page DA was developed, iteratively refined, and beta-tested. CONCLUSIONS: Using stakeholder engagement and qualitative inquiry, we developed an evidence-based DA to facilitate SDM around the question of CT scan utilization in patients with suspected uncomplicated ureterolithiasis. Future research will test the efficacy of the DA in facilitating SDM.
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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 | 0.066 | 0.143 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".