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Leveraging modified work program for infection prevention program implementation and professional development

2024· article· en· W4411689886 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Infection Control · 2024
Typearticle
Languageen
FieldNursing
TopicHealthcare Education and Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Professional developmentComputer scienceEngineering managementMedical educationEngineeringMedicine

Abstract

fetched live from OpenAlex

Background: Since the onset of the COVID-19 pandemic, the daily responsibilities of the Infection Prevention Department (IPD) have been exacerbated by heightened regulatory and licensing requirements, increasing demands from medical staff and patients, and an expanded scope of work. Consequently, infection preventionists (IPs) have struggled to find the bandwidth to effectively implement patient quality care improvement projects. The increased demand for infection prevention and control (IPAC) responsibilities has made it challenging to fill open IP positions. To address this need, a collaborative Modified Work Program (MWP) between the IPD and Human Resource Department at a National Cancer Institute-Designated Comprehensive Cancer Center has proven effective. Modified Staff for Infection Prevention (MSFIP) have been utilized to support IPD daily responsibilities with the potential development of future IPs. Methods: Injured staff were placed on modified duty by the MWP, and the IPD was contacted. An IP interviewed the MSFIP to design appropriate and accommodated responsibilities. Several tools were provided, including helpful guides, daily task lists, links, forms, agency contact information, and references. The MSFIP was granted temporary data security access to electronic medical records used by IPs. Initially, MSFIPs required orientation and shadowing by IPs. Later, MSFIP with longer recovery periods trained new MSFIP. Results: Trained MSFIPs independently managed simple IP daily tasks, allowing IPs to continue and initiate quality improvement projects. Catheter-associated urinary tract infections remained low. All MSFIP expressed a better appreciation of IP work, and several expressed interest in becoming IPs, potentially addressing the replacement of retiring IPs. Conclusion: A well-developed program for MSFIP offers several benefits. IPs should consider using MSFIPs if an MWP exists in their facility, or work on developing one in collaboration with their human resources department.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score0.569

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.039
GPT teacher head0.403
Teacher spread0.364 · 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