Continuous Wristband Monitoring Over 2 Years Decreases Identification Errors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
CONTEXT: Identification of patients is one of the first steps in ensuring the accuracy of laboratory results. In the United States, hospitalized patients wear wristbands to aid in their identification, but wristbands errors are frequently found. OBJECTIVE: To investigate if continuous monitoring of wristband errors by participants of the College of American Pathologists (CAP) Q-Tracks program results in lower wristband error rates. SETTING: A total of 217 institutions voluntarily participating in the CAP Q-Tracks interlaboratory quality improvement program in 1999 and 2000. DESIGN: Participants completed a demographic form, answered a questionnaire, collected wristband data, and at the end of the year, best and most improved performers answered another questionnaire seeking suggestions for improvement. Each institution's phlebotomists inspected wristbands for errors before performing phlebotomy and recorded the number of patients with wristband errors. On a monthly basis, participants submitted data to the CAP for data processing, and at the end of each quarter, participants received summarized comparisons. At the end of each year, participants also received a critique of the results along with suggestions for improvement. MAIN OUTCOME MEASURES: The percentage of wristband errors by quarter, types of wristband errors, and suggestions for improvement. RESULTS: During 2 years, 1 757 730 wristbands were examined, and 45 197 wristband errors were found. The participants' mean wristband error rate for the first quarter in 1999 was 7.40%; by the eighth quarter, the mean wristband error rate had fallen to 3.05% (P <.001). Continuous improvement occurred in each quarter for participants in the 1999 and 2000 program and in 7 of 8 quarters for those who participated in both 1999 and 2000. Missing wristbands accounted for 71.6% of wristband errors, and best performers usually had wristband error rates under 1.0%. The suggestion for improvement provided by the largest number of best and most improved performers was that phlebotomists should refuse to perform phlebotomy on a patient when a wristband error is detected. CONCLUSIONS: The wristband error rate decreased markedly when this rate was monitored continuously using the CAP Q-Tracks program. The Q-Tracks program provides a useful tool for improving the quality of services in anatomic pathology and laboratory medicine.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| 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 it