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Computerized physician order entry of diagnostic tests in an intensive care unit is associated with improved timeliness of service

2004· article· en· W2050562229 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCritical Care Medicine · 2004
Typearticle
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsCentre for Advancing Health OutcomesSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineOrder entryIntensive care unitComputerized physician order entryMedical emergencyService (business)Tertiary careEmergency medicineDiagnostic testMedical physicsIntensive care medicineHealth care

Abstract

fetched live from OpenAlex

OBJECTIVE: To measure the effect of computerized physician order entry on timeliness of urgent laboratory and imaging tests. DESIGN: Before-after. SETTING: Eleven-bed medical-surgical intensive care unit in a tertiary teaching hospital. PATIENTS: All patients who had "stat" laboratory or imaging tests ordered during each of two 1-month periods 10 months before and 2 months after introducing computerized physician order entry. INTERVENTIONS: Introduction of computerized physician order entry. MEASUREMENTS AND MAIN RESULTS: After computerized physician order entry was introduced, median time from ordering to obtaining laboratory specimens decreased from 77 to 21.5 mins, median time from ordering to laboratory result being reported decreased from 148 to 74 mins, and median time from ordering to imaging completed decreased from 96.5 to 29.5 mins. CONCLUSIONS: Introduction of computerized physician order entry for ordering "stat" tests in an intensive care unit is associated with improved timeliness of these tests.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.048
GPT teacher head0.394
Teacher spread0.346 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it