Effect of Triage-Based Use of the Ottawa Foot and Ankle Rules on the Number of Orders for Radiographic Imaging
Bibliographic record
Abstract
CONTEXT: Reducing unnecessary testing lessens the cost burden of medical care, but decreasing use depends on consistently following evidence-based clinical decision rules. The Ottawa foot and ankle rules (OFARs) are validated, longstanding evidence-based guidelines to predict fractures. Frequently, radiography is automatically ordered for acute ankle injuries despite findings from OFARs suggesting no fracture. OBJECTIVES: First, to determine whether implementation of protocol-driven use of the OFARs at triage would decrease the number of radiography orders and length of stay (LOS) in the emergency department. Second, to quantify the incidence of OFARs use at triage and to assess patient expectations of radiography use and patient satisfaction as rated by both patients and clinicians. METHODS: In this prospective, 2-stage sequential pilot study, patients with acute ankle and foot injuries were screened in the emergency department between January 2013 and October 2013. In the first stage, clinicians (physician assistants, residents, and attending physicians) performed their usual practice habits for radiography use in the control group. For the second stage, they were educated to appropriately apply the OFARs before ordering radiography. For patients who were suspected of having a fracture at triage, nursing staff ordered radiography. For patients who were not suspected of having a fracture at triage, a clinician reassessed them using the OFARs after their triage assessment. Radiography was then ordered at the discretion of the clinician. Results gathered after training in the OFARs comprised the intervention group. After discharge, patients were surveyed regarding their expectations and satisfaction, and clinicians were surveyed on their perceptions of patient satisfaction. RESULTS: A total of 131 patients were screened, 62 patients were enrolled in the study after consent was obtained, and 2 patients withdrew from the study prematurely, leaving 30 patients in each group. Fifty-eight of the 60 patients (97%) underwent radiography. Emergency department LOS decreased from 103 minutes to 96.5 minutes (P=.297) after the OFARs were applied. There was also a decrease in LOS in patients with a fracture (137 minutes vs 103 minutes [P=.112]). Radiography was expected to be ordered by 27 of 30 patients in the control group (90%) and 24 of 30 in the intervention group (80%) (P=.472). Patients were equally satisfied among the groups (54 of 60 [90%]) (with no difference between groups), and 27 of 30 (90%) vs 30 of 30 (100%) clinicians in the control and intervention groups, respectively, perceived that patients were satisfied with their treatment. CONCLUSION: There was no statistical evidence that application of the OFARs decreases the number of imaging orders or decreases LOS. This observation suggests that even when clinicians are being observed and instructed to use clinical decision rules, their evaluation bias tends toward recommendations for testing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".