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Record W4309821734 · doi:10.1136/bmjoq-2022-002052

Stopping routine urine screening studies for stroke rehabilitation inpatient admissions

2022· article· en· W4309821734 on OpenAlexafffund
Arjun Ghuman, Pamela Mathura, Jaime C. Yu

Bibliographic record

VenueBMJ Open Quality · 2022
Typearticle
Languageen
FieldMedicine
TopicUrinary Tract Infections Management
Canadian institutionsAlberta Health ServicesUniversity of Alberta
FundersGlenrose Rehabilitation Hospital
KeywordsMedicineUrineAuditStroke (engine)RehabilitationEmergency medicineUrinary systemUrodynamic testingAsymptomaticPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Urine testing on asymptomatic patients is not aligned with guidelines; however, stroke survivors have trouble communicating symptoms, and urinary tract infections (UTIs) are a recognised poststroke complication. All stroke inpatients at a tertiary rehabilitation hospital underwent urine testing on admission. We led a quality improvement (QI) project on one stroke rehabilitation unit aimed to reduce admission urine testing from 100% to 0%. Baseline audit representing 2 weeks of admissions identified 27 of 28 patients had urine tests; however, none required UTI treatment despite 3 positive culture results. Estimated cost of testing was $C675. QI tools identified that a standardised paper-based admission form facilitated automatic urine testing. Project intervention strategies included education, clinicians crossing off urine orders and unit clerks flagging unaddressed orders for reassessment. A chart audit after 4 weeks and prescriber survey after 6 months assessed impact. Postintervention audit (n=23) revealed 1 patient had admission urine tests, 22 orders were crossed out, 1 chart was flagged and estimated testing cost declined from $C675 to $C25. Six urine tests were completed after admission and two patients required UTI treatment. Post 6 months, unit clerks assumed the role to cross out the order on the standardised form, and no patient had routine admission urine testing. There was no clinical benefit in screening for UTIs prior to stroke rehabilitation. This project is a practical example of deadopting a practice promoted by standardised order forms.

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.

How this classification was reachedexpand

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.303
GPT teacher head0.536
Teacher spread0.233 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes2
Has abstractyes

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