MétaCan
Menu
Back to cohort
Record W4386316434 · doi:10.1097/qmh.0000000000000427

Reduction of Chest Drain Overuse Through Implementation of a Pleural Drainage Order Set

2023· article· en· W4386316434 on OpenAlex
Pattraporn Tajarernmuang, David Valenti, Anne V. Gonzalez, Giovanni Artho, Mary Tsatoumas, Stéphane Beaudoin

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

VenueQuality Management in Health Care · 2023
Typearticle
Languageen
FieldMedicine
TopicPleural and Pulmonary Diseases
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineThoracentesisDrainageSurgeryPleural diseasePleural effusionRespiratory diseaseInternal medicineLung

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Small chest drains are used in many centers as the default drainage strategy for various pleural effusions. This can lead to drain overuse, which may be harmful. This study aimed to reduce chest drain overuse. METHODS: We studied consecutive pleural procedures performed in the radiology department before (August 1, 2015, to July 31, 2016) and after intervention (September 1, 2019, to January 31, 2020). Chest drains were deemed indicated or not based on criteria established by a local interdisciplinary work group. The intervention consisted of a pleural drainage order set embedded in electronic medical records. It included indications for chest drain insertion, prespecified drain sizes for each indication, fluid analyses, and postprocedure radiography orders. Overall chest drain use and proportion of nonindicated drains were the outcomes of interest. RESULTS: We reviewed a total of 288 procedures (pre-intervention) and 155 procedures (post-intervention) (thoracentesis and drains). Order-set implementation led to a reduction in drain use (86.5% vs 54.8% of all procedures, P < .001) and reduction in drain insertions in the absence of an indication (from 45.4% to 29.4% of drains, P = .01). The need for repeat procedures did not increase after order-set implementation (22.0% pre vs 17.7% post, P = .40). Complication rates and length of hospital stay did not differ significantly after the intervention. More pleural infections were treated with drain sizes of 12Fr and greater (31 vs 70%, P < .001) after order-set deployment, and direct procedural costs were reduced by 27 CAN$ per procedure. CONCLUSION: Implementation of a pleural drainage order-set reduced chest drain use, improved procedure selection according to clinical needs, and reduced direct procedural costs. In institutions where small chest drains are used as the default drainage strategy for pleural effusions, this order set can reduce chest drain overuse.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.609
Threshold uncertainty score0.571

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.093
GPT teacher head0.450
Teacher spread0.356 · 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