What can Canada learn from the USA's experience in reducing healthcare‐associated infections?
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.
Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it