Effect of Departmental and Physician-Selected Interventions on Point-of-Care Ultrasound Documentation Completion
Bibliographic record
Abstract
Background Point-of-care ultrasound (POCUS) has been disruptive to many experienced emergency physicians as it requires competence in a new physical skill, real-time image interpretation, and navigation of novel software for submission to the electronic health record (EHR). Incomplete documentation of a performed POCUS study used for clinical decision-making represents a potential medicolegal liability, may expose the patient to repetitive or potentially unnecessary imaging, and is a missed opportunity for reimbursement. Identifying effective facilitators of ED POCUS documentation completion requires additional investigation. Methods In the first part of this mixed-methods study, eligible attending physicians were stratified into levels of use ("high"/"low"/"never") based on recent POCUS documentation performance. Semi-structured interviews were conducted with high and low utilizers to explore their perceptions of the POCUS submission workflow and their receptivity to various proposed interventions. Qualitative data were analyzed using a thematic analysis that explored perceived usefulness and usability. The second part of the study consisted of two intervention phases. First, physicians achieving minimum POCUS documentation numbers were rewarded with additional shift scheduling flexibility. In the second phase, the intervention that garnered the most interview support, daily documentation reminder emails, was implemented. The primary outcome was the individual POCUS documentation rates calculated as all studies submitted divided by all studies performed (submitted plus unsubmitted) per month. Provider-level monthly data was aggregated into a departmental rate. Results Interviews were conducted with 12 physicians, six from the highest and six from the lowest documentation quartiles. Both groups supported the same two proposed interventions: reminder emails ranked first, then monetary rewards ranked second. High utilizers emphasized the clinical utility of POCUS, whereas low utilizers expressed concerns over "double billing" and exposure to medicolegal liability with uncertain scan interpretations. For low utilizers, a documentation decision could be dependent on the performing resident physician's displayed confidence. Both groups voiced frustration with the need to use a separate program, Qpath (Telexy Healthcare, Inc, Maple Ridge, British Columbia, Canada), for POCUS documentation. During intervention phase one, the aggregate departmental documentation rate increased from 44.6% to 60.1% with the introduction of the schedule request incentive. This improvement was seen across all documentation quartiles. The departmental rate remained stable and did not improve further following the addition of the daily documentation reminder emails in intervention phase two. When reminder emails ceased yet the day-off request incentive continued, the departmental rate did not drop. Conclusions The implementation of a non-financial shift scheduling incentive correlated with the largest increase in departmental POCUS documentation rate. Interviewees incorrectly predicted that email reminders would be the most influential intervention highlighting a mismatch between physician perception and effective drivers of behavior change. Further investigation may focus on determining the size and longevity of the isolated impact of a schedule request incentive, as one might expect diminishing marginal utility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".