Reducing inappropriate transthoracic echocardiography orders in normotensive patients with acute pulmonary embolism in a community hospital: a quality improvement project
Bibliographic record
Abstract
Transthoracic echocardiograms (TTEs) have limited value in guiding management of normotensive patients with acute pulmonary embolism (PE). Nevertheless, TTEs are frequently ordered inappropriately. This quality improvement project aimed to decrease inappropriate TTE orders by 30% over 6 months in patients with PE admitted to general internal medicine at a community hospital. Two interventions were implemented using successive plan-do-study-act (PDSA) cycles: educational sessions for physicians and the distribution of TTE-ordering algorithms for triaging of TTE appropriateness. Four audits on TTE orders for inpatients with PE were conducted throughout the project: a pre-intervention audit (pre-audit; March to August 2020), a post-intervention 1 audit (post-I1; August to September 2022), a post-intervention 2 audit (post-I2; December 2022 to February 2023) and a post-intervention audit (post-audit; March to August 2023). The primary outcome measure was the proportion of inappropriate to appropriate TTE orders during the pre-intervention and post-intervention periods. During the pre-audit, post-I1, post-I2 and post-audit periods, 89, 23, 20 and 158 patients, respectively, were admitted with PEs. 37, 10, 3 and 14 patients in each of these periods, respectively, received a TTE for PE-related reasons and were therefore included in the audits. 42%, 43%, 15% and 24% of patients, respectively, received a TTE for PE-related reasons. 89%, 50%, 67% and 79% of those TTEs, respectively, were inappropriate. There was a transient decrease in inappropriate to appropriate TTE orders ratio after the first intervention (p<0.005). Inappropriate investigations lead to additional healthcare costs and delays in patient care. This quality improvement project highlights an ongoing need to increase awareness surrounding TTE indications to improve appropriate utilisation. Next steps include further PDSA cycles with additional interventions to continue to try and decrease inappropriate TTE orders in the community hospital setting.
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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 | 0.025 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".