Recurring Critical Results and Their Impact on the Volume of Critical Calls at a Tertiary Care Center
Bibliographic record
Abstract
BACKGROUND: When a test result is critically abnormal, laboratories notify the responsible caregivers immediately, usually with a phone call. If the same test was ordered repeatedly, our institution has a policy of not notifying the caregiver if the previous result was also critical and within 24 h. We compared our policy with those of several different laboratories in North America and estimated the impact of changing our current policy to calling for all critical results, regardless of the time interval. METHODS: Several North American laboratories (n = 15) were surveyed regarding their critical result notification policy. For our institution, we performed a retrospective analysis focusing on critical values in a 5-month period for common chemistry tests. We estimated the effect on volume of calls and the impact on workload with regard to changing the critical result notification policy and critical thresholds. RESULTS: A majority of surveyed laboratories had some form of restriction for calling about recurring critical results. In our institution, removing the restrictions would increase the average number of daily calls by 11%-155%, depending on the analyte. The choice of critical thresholds also has an effect on the number of calls, and the effect depends on the analyte and the threshold chosen. CONCLUSIONS: Guidelines do not specify how recurring critical results should be communicated. Depending on the institutional resources, some laboratories call only the first critical result for one or more tests if certain criteria are met. Modification of these policies can lead to significant changes in the volume of calls made by the laboratory and can have numerous impacts related to workload, logistics, and patient care.
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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 | 0.004 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".