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Record W2062200089 · doi:10.1371/journal.pmed.1001268

Reduction in Clostridium difficile Infection Rates after Mandatory Hospital Public Reporting: Findings from a Longitudinal Cohort Study in Canada

2012· article· en· W2062200089 on OpenAlexafffundabout
Nick Daneman, Thérèse A. Stukel, Xiaomu Ma, Marian J. Vermeulen, Astrid Guttmann

Bibliographic record

VenuePLoS Medicine · 2012
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsHospital for Sick ChildrenHealth Sciences CentreUniversity of TorontoSunnybrook Health Science CentreInstitute for Clinical Evaluative Sciences
FundersCanadian Institutes of Health ResearchOntario Ministry of Health and Long-Term CareInstitute for Clinical Evaluative Sciences
KeywordsClostridium difficileMedicinePopulationCohort studyPublic healthEnvironmental healthClostridium Difficile ColitisClostridium InfectionsC difficileEmergency medicineInternal medicineMicrobiologyPathologyBiologyAntibiotics

Abstract

fetched live from OpenAlex

BACKGROUND: The role of public reporting in improving hospital quality of care is controversial. Reporting of hospital-acquired infection rates has been introduced in multiple health care systems, but its relationship to infection rates has been understudied. Our objective was to determine whether mandatory public reporting by hospitals is associated with a reduction in hospital rates of Clostridium difficile infection. METHODS AND FINDINGS: We conducted a longitudinal, population-based cohort study in Ontario (Canada's largest province) between April 1, 2002, and March 31, 2010. We included all patients (>1 y old) admitted to 180 acute care hospitals. Using Poisson regression, we developed a model to predict hospital- and age-specific monthly rates of C. difficile disease per 10,000 patient-days prior to introduction of public reporting on September 1, 2008. We then compared observed monthly rates of C. difficile infection in the post-intervention period with rates predicted by the pre-intervention predictive model. In the pre-intervention period there were 33,634 cases of C. difficile infection during 39,221,113 hospital days, with rates increasing from 7.01 per 10,000 patient-days in 2002 to 10.79 in 2007. In the first calendar year after the introduction of public reporting, there was a decline in observed rates of C. difficile colitis in Ontario to 8.92 cases per 10,000 patient-days, which was significantly lower than the predicted rate of 12.16 (95% CI 11.35-13.04) cases per 10,000 patient-days (p<0.001). Over this period, public reporting was associated with a 26.7% (95% CI 21.4%-31.6%) reduction in C. difficile cases, or a projected 1,970 cases averted per year (95% CI 1,476-2,500). The effect was specific to C. difficile, with rates of community-acquired gastrointestinal infections and urinary tract infections unchanged. A limitation of our study is that this observational study design cannot rule out the influence of unmeasured temporal confounders. CONCLUSIONS: Public reporting of hospital C. difficile rates was associated with a substantial reduction in the population burden of this infection. Future research will be required to discern the direct mechanism by which C. difficile infection rates may have been reduced in response to public reporting. Please see later in the article for the Editors' Summary.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.026
Threshold uncertainty score0.187

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.100
GPT teacher head0.393
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations56
Published2012
Admission routes3
Has abstractyes

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