Prior studies evaluating the impact of discontinuation of contact precautions (DcCP) on methicillin-resistant Staphylococcus aureus (MRSA) outcomes have characterized all healthcare-associated infections (HAIs) rather than those likely preventable by contact precautions. We aimed to analyze the impact of DcCP on the rate of MRSA HAI including transmission events identified through whole genome sequencing (WGS) surveillance.

Quasi experimental interrupted time series.

Acute care medical center.

Inpatients.

The effect of DcCP (use of gowns and gloves) for encounters among patients with MRSA carriage was evaluated using time series analysis of MRSA HAI rates from January 2019 through December 2022, compared to WGS-defined attributable transmission events before and after DcCP in December 2020.

The MRSA HAI rate was 4.22/10,000 patient days before and 2.98/10,000 patient days after DcCP (incidence rate ratio [IRR] 0.71 [95% confidence interval 0.56–0.89]) with a significant immediate decrease (P = .001). There were 7 WGS-defined attributable transmission events before and 11 events after DcCP (incident rate ratio 0.90 [95% confidence interval 0.30–2.55]).

DcCP did not result in an increase in MRSA HAI or, in WGS-defined attributable transmission events. Comprehensive analyses of the effect of transmission prevention measures should include outcomes specifically measuring transmission-associated HAI.

To describe a novel attribution metric estimating the causal source location of healthcare-associated Clostridioides difficile and compare it with the current US National Healthcare Safety Network (NHSN) surveillance reporting standard.

Quality improvement study.

Two acute care facilities.

A novel attribution metric assigned days of attribution to locations where patients were located for 14 days before and the day of their C. difficile diagnosis. We correlated the NHSN-assigned unit attribution with the novel attribution measure and compared the proportion of attribution assigned to inpatient units.

During a 30-month period, there were 727 NHSN C. difficile healthcare-associated infections (HAIs) and 409 non-HAIs; the novel metric attributed 17,034 days. The correlation coefficients for NHSN and novel attributions among non-ICU units were 0.79 (95% CI, 0.76–0.82) and 0.74 (95% CI, 0.70–0.78) and among ICU units were 0.70 (95% CI, 0.63–0.76) and 0.69 (95% CI, 0.60–0.77) at facilities A and B, respectively. The distribution of difference in percent attribution showed higher inpatient unit attribution using NHSN measure than the novel attribution metric: 38% of ICU units and 15% of non-ICU units in facility A, and 20% of ICU units and 25% of non-ICU units in facility B had a median difference >0; no inpatient units showed a greater attribution using the novel attribution metric.

The novel attribution metric shifts attribution from inpatient units to other settings and correlates modestly with NHSN methodology of attribution. If validated, the attribution metric may more accurately target C. difficile reduction efforts.

To assess the impact of a 24-hour autocancellation of uncollected Clostridioides difficile samples in reducing reported healthcare-associated infections (HAIs).

Quality-improvement, before-and-after implementation study.

The study was conducted in 17 hospitals in Pennsylvania.

Clostridioides difficile tests that are not collected within 24 hours are automatically canceled (“autocancel”) through the electronic health record. The intervention took place at 2 facilities (intervention period November 2021–July 2022) and subsequently at 15 additional facilities (April 2022–July 2022). Quality measures included percentage of orders canceled, C. difficile HAI rate, percent positivity of completed tests, and potential adverse outcomes of canceled or delayed testing.

Of 6,101 orders, 1,090 (17.9%) were automatically canceled after not being collected for 24 hours during the intervention periods. The reported C. difficile HAI rates per 10,000 patient days did not significantly change. These rates were 8.07 in the 6-month preintervention period and 8.77 in the intervention period for facilities A and B combined (incidence rate ratio [IRR], 1.09; 95% CI, 0.88–1.34; P = .43), and were 5.23 HAIs per 10,000 patient days in the 6-month preintervention period and 5.33 in the intervention period for facilities C–Q combined (IRR, 1.02; 95% CI, 0.79–1.32; P = .87). From the preintervention to the intervention periods, the percent positivity rates of completed C. difficile tests increased by 1.1% for facilities A and B and by 1.4% for facilities C–Q. No adverse outcomes were observed.

The 24-hour autocancellation of uncollected C. difficile orders reduced testing but did not result in reported HAI reduction.

To evaluate the impact of a diagnostic stewardship intervention on Clostridioides difficile healthcare-associated infections (HAI).

Quality improvement study.

Two urban acute care hospitals.

All inpatient stool testing for C. difficile required review and approval prior to specimen processing in the laboratory. An infection preventionist reviewed all orders daily through chart review and conversations with nursing; orders meeting clinical criteria for testing were approved, orders not meeting clinical criteria were discussed with the ordering provider. The proportion of completed tests meeting clinical criteria for testing and the primary outcome of C. difficile HAI were compared before and after the intervention.

The frequency of completed C. difficile orders not meeting criteria was lower [146 (7.5%) of 1,958] in the intervention period (January 10, 2022–October 14, 2022) than in the sampled 3-month preintervention period [26 (21.0%) of 124; P < .001]. C. difficile HAI rates were 8.80 per 10,000 patient days prior to the intervention (March 1, 2021–January 9, 2022) and 7.69 per 10,000 patient days during the intervention period (incidence rate ratio, 0.87; 95% confidence interval, 0.73–1.05; P = .13).

A stringent order-approval process reduced clinically nonindicated testing for C. difficile but did not significantly decrease HAIs.

To evaluate variables that affect risk of contamination for endoscopic retrograde cholangiopancreatography and endoscopic ultrasound endoscopes.

Observational, quality improvement study.

University medical center with a gastrointestinal endoscopy service performing ∼1,000 endoscopic retrograde cholangiopancreatography and ∼1,000 endoscopic ultrasound endoscope procedures annually.

Duodenoscope and linear echoendoscope sampling (from the elevator mechanism and instrument channel) was performed from June 2020 through September 2021. Operational changes during this period included standard reprocessing with high-level disinfection with ethylene oxide gas sterilization (HLD–ETO) was switched to double high-level disinfection (dHLD) (June 16, 2020–July 15, 2020), and duodenoscopes changed to disposable tip model (March 2021). The frequency of contamination for the co-primary outcomes were characterized by calculated risk ratios.

The overall pathogenic contamination rate was 4.72% (6 of 127). Compared to duodenoscopes, linear echoendoscopes had a contamination risk ratio of 3.64 (95% confidence interval [CI], 0.69–19.1). Reprocessing using HLD-ETO was associated with a contamination risk ratio of 0.29 (95% CI, 0.06–1.54). Linear echoendoscopes undergoing dHLD had the highest risk of contamination (2 of 18, 11.1%), and duodenoscopes undergoing HLD-ETO and the lowest risk of contamination (0 of 53, 0%). Duodenoscopes with a disposable tip had a 0% contamination rate (0 of 27).

We did not detect a significant reduction in endoscope contamination using HLD-ETO versus dHLD reprocessing. Linear echoendoscopes have a risk of contamination similar to that of duodenoscopes. Disposable tips may reduce the risk of duodenoscope contamination.

Identifying routes of transmission among hospitalized patients during a healthcare-associated outbreak can be tedious, particularly among patients with complex hospital stays and multiple exposures. Data mining of the electronic health record (EHR) has the potential to rapidly identify common exposures among patients suspected of being part of an outbreak.

We retrospectively analyzed 9 hospital outbreaks that occurred during 2011–2016 and that had previously been characterized both according to transmission route and by molecular characterization of the bacterial isolates. We determined (1) the ability of data mining of the EHR to identify the correct route of transmission, (2) how early the correct route was identified during the timeline of the outbreak, and (3) how many cases in the outbreaks could have been prevented had the system been running in real time.

Correct routes were identified for all outbreaks at the second patient, except for one outbreak involving >1 transmission route that was detected at the eighth patient. Up to 40 or 34 infections (78% or 66% of possible preventable infections, respectively) could have been prevented if data mining had been implemented in real time, assuming the initiation of an effective intervention within 7 or 14 days of identification of the transmission route, respectively.

Data mining of the EHR was accurate for identifying routes of transmission among patients who were part of the outbreak. Prospective validation of this approach using routine whole-genome sequencing and data mining of the EHR for both outbreak detection and route attribution is ongoing.

Recovery of multidrug-resistant (MDR) Pseudomonas aeruginosa and Klebsiella pneumoniae from a cluster of patients in the medical intensive care unit (MICU) prompted an epidemiologic investigation for a common exposure.

Clinical and microbiologic data from MICU patients were retrospectively reviewed, MICU bronchoscopes underwent culturing and borescopy, and bronchoscope reprocessing procedures were reviewed. Bronchoscope and clinical MDR isolates epidemiologically linked to the cluster underwent molecular typing using pulsed-field gel electrophoresis (PFGE) followed by whole-genome sequencing.

Of the 33 case patients, 23 (70%) were exposed to a common bronchoscope (B1). Both MDR P. aeruginosa and K. pneumonia were recovered from the bronchoscope’s lumen, and borescopy revealed a luminal defect. Molecular testing demonstrated genetic relatedness among case patient and B1 isolates, providing strong evidence for horizontal bacterial transmission. MDR organism (MDRO) recovery in 19 patients was ultimately linked to B1 exposure, and 10 of 19 patients were classified as belonging to an MDRO pseudo-outbreak.

Surveillance of bronchoscope-derived clinical culture data was important for early detection of this outbreak, and whole-genome sequencing was important for the confirmation of findings. Visualization of bronchoscope lumens to confirm integrity should be a critical component of device reprocessing.