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Quality Improvement Initiatives for Pleural Infection Managed with Intrapleural Therapy

2024· article· en· W4404076730 on OpenAlexaffabout
Riham Elmahboubi, Catherine Robitaille, Céline Dupont, Julie Dallaire, Marie Létourneau, Christian Sirois, David Valenti, Anne V. Gonzalez, Stéphane Beaudoin

Bibliographic record

VenueAnnals of the American Thoracic Society · 2024
Typearticle
Languageen
FieldMedicine
TopicPleural and Pulmonary Diseases
Canadian institutionsSanté MontérégieCentre intégré de santé et de services sociaux de la Montérégie-CentreMcGill University Health CentreCégep de LévisCegep de Saint Jerome
Fundersnot available
KeywordsMedicineQuality managementIntensive care medicineMEDLINEOperations management

Abstract

fetched live from OpenAlex

Abstract Rationale Pleural infection is associated with significant mortality, and its management is complex. Little attention has been given to care-process metrics such as management delays, pleural drainage practices, and adequacy of intrapleural therapy administration despite their potential impact on outcomes. Audits revealed gaps in those care processes in our institution. Objectives To assess the impact of quality-improvement initiatives on pleural effusion management in adults. Methods We performed a retrospective comparison of patients treated with intrapleural therapy for pleural infection at the McGill University Health Center before (April 2013 to April 2016; N = 109) and after interventions (June 2020 to June 2021; N = 44). Interventions included a pleural drainage policy and order set, an intrapleural therapy protocol and preprinted order, implementation of intrapleural therapy administration by nurses, local pleural infection guideline development, and an online learning module for physicians. Major outcomes (length of stay, mortality, surgical treatment) and care-process metrics (management delays, pleural drainage practices, intrapleural therapy administration) were compared between the two periods. Results After implementation of the interventions, in-hospital mortality and length of stay were unchanged, but the incidence of surgical management went from 14% to 0% (P = 0.01). Delays in drain insertion and intrapleural therapy initiation were not significantly different. Insertion of drains smaller than 12 F decreased from 51% to 7% (P < 0.001). Drain blockage decreased from 20% to 2% (P = 0.004). The incidence of additional drain insertion went from 62% to 48% (P = 0.12). After interventions, 70% of intrapleural therapy doses were given by nurses, the intrapleural therapy protocol was more often adequately followed, fewer doses were missed, and less extended therapy was prescribed. Complications related to drain insertion and intrapleural therapy were similar between the two periods. Conclusions After the implementation of multifaceted quality improvement interventions for pleural infection including the involvement of nurses in pleural drain flushing and intrapleural therapy, improvements were observed in intrapleural therapy administration, chest drainage practices, and need for surgery. However, length of stay, mortality, and management delays were unchanged.

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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)0.000
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 score0.861
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
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 head0.118
GPT teacher head0.436
Teacher spread0.318 · 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".

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Citations2
Published2024
Admission routes2
Has abstractyes

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