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Record W2066145344 · doi:10.1108/14777271211220862

What can Canada learn from the USA's experience in reducing healthcare‐associated infections?

2012· article· en· W2066145344 on OpenAlex
William R. Jarvis

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueClinical Governance An International Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicInfection Control in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsReimbursementMedicineHealth careMedicaidInfection controlHarmMedical emergencyCommissionFamily medicineNursingBusinessIntensive care medicinePolitical scienceFinance

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to briefly review the history of healthcare‐associated infection (HAI) prevention programs in the USA since the early 1970s until today, and provide suggestions how other countries (and Canada specifically) may learn from this experience to accelerate HAI prevention and patient safety improvements in their counties. Design/methodology/approach The paper is a narrative review of literature and personal experience. Findings US hospitals have had healthcare‐associated infection (HAI) prevention programs, including surveillance for selected HAIs, since the late 1960s‐early 1970s. Such programs began with active surveillance for HAIs based upon the Centers for Disease Control and Prevention's (CDCs) National Nosocomial Infections Surveillance (NNIS) system. This system included standardized definitions and surveillance protocols. Since the 1980s, the CDC has developed HAI prevention guidelines, with categorized recommendations for HAI prevention. In the early 2000s, the Institute of Medicine published a report outlining the harm caused by HAIs. This led to increased attention to HAI prevention by an increasingly wide variety of organizations. The Joint Commission and the Centers for Medicare and Medicaid Services (CMS) initiated HAI prevention efforts. Many studies documented the failure of hospitals to fully implement evidence‐based practices. The increased attention to HAIs and their morbidity and mortality led to media reports and ultimately an initiative by the Consumer's Union for mandatory reporting of HAI rates by hospitals in all states. Subsequently, the CMS introduced decreased reimbursement for the additional costs directly related to HAIs (and other critical incidents) and linkage of reimbursement levels to hospital HAI rates. Together, mandatory reporting and reduced reimbursement for HAIs has led hospital executives to focus more attention on infection control programs to decrease HAI rates. Progress on preventing HAIs seems to be related to standardizing evidence‐based HAI prevention bundles, mandatory reporting, and paying for performance (or not paying for preventable HAI complications). Given that voluntary HAI prevention programs have existed since the 1970s, it appears that regulation, reporting, and decreased reimbursement has resulted in more rapid implementation of HAI prevention programs and improved patient safety. Practical implications The different major activities enhancing HAI prevention in the USA are outlined in an historic context. Originality/value Understanding the history of progress in hospital infection control efforts provides an essential perspective for policy makers and for the interdisciplinary team required to evaluate HAI mandatory public reporting in a comprehensive manner.

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)0.005
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 score0.165
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.109
GPT teacher head0.448
Teacher spread0.339 · 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