Frequency that Laboratory Tests Influence Medical Decisions
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
BACKGROUND: Among the variables that influence medical decisions, laboratory tests are considered to be among the most important and frequently used. The influence of laboratory tests on medical decisions has been difficult to estimate. The goal of this study was to estimate the number of patient encounters that included a laboratory test. METHODS: We extracted information for 72196 patient encounters from 1-week intervals each quarter of a year from our comprehensive academic medical center electronic medical record. The patients examined represent a comprehensive range of clinical conditions and medical services. We determined for which encounters laboratory and other orders existed. RESULTS: Overall 35% of encounters had 1 or more laboratory tests ordered. However, the percent varied markedly with patient care areas. For inpatient, emergency department, and outpatient populations, 98%, 56%, and 29%, respectively, had 1 or more laboratory tests ordered. CONCLUSIONS: Our observations support that it is not possible to use a single number to categorize the frequency with which laboratory tests occur in patient encounters. Utilization of laboratory tests varied with type of medical service with almost all inpatients, approximately half of emergency department patients, and nearly one-third of outpatients having laboratory tests during their healthcare visit.
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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 | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it