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 develop, implement, and evaluate the effectiveness of a unique centralized surveillance infection prevention (CSIP) program.

Observational quality improvement project.

An integrated academic healthcare system.

The CSIP program comprises senior infection preventionists who are responsible for healthcare-associated infection (HAI) surveillance and reporting, allowing local infection preventionists (LIPs) a greater portion of their time to non-surveillance patient safety activities. Four CSIP team members accrued HAI responsibilities at 8 facilities.

We evaluated the effectiveness of the CSIP program using 4 measures: recovery of LIP time, efficiency of surveillance activities by LIPs and CSIP staff, surveys characterizing LIP perception of their effectiveness in HAI reduction, and nursing leaders’ perception of LIP effectiveness.

The amount of time spent by LIP teams on HAI surveillance was highly variable, while CSIP time commitment and efficiency was steady. Post-CSIP implementation, 76.9% of LIPs agreed that they spend adequate time on inpatient units, compared to 15.4% pre-CSIP; LIPs also reported more time to allot to non-surveillance activities. Nursing leaders reported greater satisfaction with LIP involvement with HAI reduction practices.

CSIP programs are a little-reported strategy to ease burden on LIPs with reallocation of HAI surveillance. The analyses presented here will aid health systems in anticipating the benefit of CSIP programs.

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.

To evaluate the effectiveness of ultraviolet-C (UV-C) disinfection as an adjunct to standard chlorine-based disinfectant terminal room cleaning in reducing transmission of hospital-acquired multidrug-resistant organisms (MDROs) from a prior room occupant.

A retrospective cohort study was conducted to compare rates of MDRO transmission by UV-C status from January 1, 2016, through December 31, 2018.

Acute-care, single-patient hospital rooms at 6 hospitals within an academic healthcare system in Pennsylvania.

Transmission of hospital-acquired MDRO infection was assessed in patients subsequently assigned to a single-patient room of a source occupant with carriage of 1 or more MDROs on or during admission. Acquisition of 5 pathogens was compared between exposed patients in rooms with standard-of-care chlorine-based disinfectant terminal cleaning with or without adjunct UV-C disinfection. Logistic regression analysis was used to estimate the adjusted risk of pathogen transfer with adjunctive use of UV-C disinfection.

In total, 33,771 exposed patient admissions were evaluated; the source occupants carried 46,688 unique pathogens. Prior to the 33,771 patient admissions, 5,802 rooms (17.2%) were treated with adjunct UV-C disinfection. After adjustment for covariates, exposed patients in rooms treated with adjunct UV-C were at comparable risk of transfer of any pathogen (odds ratio, 1.06; 95% CI, 0.84–1.32; P = .64).

Our analysis does not support the use of UV-C in addition to post-discharge cleaning with chlorine-based disinfectant to lower the risk of prior room occupant pathogen transfer.

To evaluate infectious pathogen transmission data visualizations in outbreak publications.

Scoping review.

Medline was searched for outbreak investigations of infectious diseases within healthcare facilities that included ≥1 data visualization of transmission using data observable by an infection preventionist showing temporal and/or spatial relationships. Abstracted data included the nature of the cluster(s) (pathogen, scope of transmission, and individuals involved) and data visualization characteristics including visualization type, transmission elements, and software.

From 1,957 articles retrieved, we analyzed 30 articles including 37 data visualizations. The median cluster size was 20.5 individuals (range, 7–1,963) and lasted a median of 214 days (range, 12–5,204). Among the data visualization types, 10 (27%) were floor-plan transmission maps, 6 (16%) were timelines, 11 (30%) were transmission networks, 3 (8%) were Gantt charts, 4 (11%) were cluster map, and 4 (11%) were other types. In addition, 26 data visualizations (70%) contained spatial elements, 26 (70%) included person type, and 19 (51%) contained time elements. None of the data visualizations contained contagious periods and only 2 (5%) contained symptom-onset date.

The data visualizations of healthcare-associated infectious disease outbreaks in the systematic review were diverse in type and visualization elements, though no data visualization contained all elements important to deriving hypotheses about transmission pathways. These findings aid in understanding the visualizing transmission pathways by describing essential elements of the data visualization and will inform the creation of a standardized mapping tool to aid in earlier initiation of interventions to prevent transmission.

Whole-genome sequencing (WGS) has traditionally been used in infection prevention to confirm or refute the presence of an outbreak after it has occurred. Due to decreasing costs of WGS, an increasing number of institutions have been utilizing WGS-based surveillance. Additionally, machine learning or statistical modeling to supplement infection prevention practice have also been used. We systematically reviewed the use of WGS surveillance and machine learning to detect and investigate outbreaks in healthcare settings.

We performed a PubMed search using separate terms for WGS surveillance and/or machine-learning technologies for infection prevention through March 15, 2021.

Of 767 studies returned using the WGS search terms, 42 articles were included for review. Only 2 studies (4.8%) were performed in real time, and 39 (92.9%) studied only 1 pathogen. Nearly all studies (n = 41, 97.6%) found genetic relatedness between some isolates collected. Across all studies, 525 outbreaks were detected among 2,837 related isolates (average, 5.4 isolates per outbreak). Also, 35 studies (83.3%) only utilized geotemporal clustering to identify outbreak transmission routes. Of 21 studies identified using the machine-learning search terms, 4 were included for review. In each study, machine learning aided outbreak investigations by complementing methods to gather epidemiologic data and automating identification of transmission pathways.

WGS surveillance is an emerging method that can enhance outbreak detection. Machine learning has the potential to identify novel routes of pathogen transmission. Broader incorporation of WGS surveillance into infection prevention practice has the potential to transform the detection and control of healthcare outbreaks.

To define conditions in which contact precautions can be safely discontinued for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus (VRE).

Interrupted time series.

15 acute-care hospitals.

Inpatients.

Contact precautions for endemic MRSA and VRE were discontinued in 12 intervention hospitals and continued at 3 nonintervention hospitals. Rates of MRSA and VRE healthcare-associated infections (HAIs) were collected for 12 months before and after. Trends in HAI rates were analyzed using Poisson regression. To predict conditions when contact precautions may be safely discontinued, selected baseline hospital characteristics and infection prevention practices were correlated with HAI rate changes, stratified by hospital.

Aggregated HAI rates from intervention hospitals before and after discontinuation of contact precautions were 0.14 and 0.15 MRSA HAI per 1,000 patient days (P = .74), 0.05 and 0.05 VRE HAI per 1,000 patient days (P = .96), and 0.04 and 0.04 MRSA laboratory-identified (LabID) events per 100 admissions (P = .57). No statistically significant rate changes occurred between intervention and non-intervention hospitals. All successful hospitals had low baseline MRSA and VRE HAI rates and high hand hygiene adherence. We observed no correlations between rate changes after discontinuation and the assessed hospital characteristics and infection prevention factors, but the rate improved with higher proportion of semiprivate rooms (P = .04).

Discontinuing contact precautions for MRSA/VRE did not result in increased HAI rates, suggesting that contact precautions can be safely removed from diverse hospitals, including community hospitals and those with lower proportions of private rooms. Good hand hygiene and low baseline HAI rates may be conditions permissive of safe removal of contact precautions.

To describe interfacility transfer communication (IFTC) methods for notification of multidrug-resistant organism (MDRO) status in a diverse sample of acute-care hospitals.

Cross-sectional survey.

Hospitals within the Society for Healthcare Epidemiology of America (SHEA) Research Network (SRN).

SRN members completed an electronic survey on protocols and methods for IFTC. We assessed differences in IFTC frequency, barriers, and perceived benefit by presence of an IFTC protocol.

Among 136 hospital representatives who were sent the survey, 54 (40%) responded, of whom 72% reported having an IFTC protocol in place. The presence of a protocol did not differ significantly by hospital size, academic affiliation, or international status. Of those with IFTC protocols, 44% reported consistent notification of MDRO status (>75% of the time) to receiving facilities, as opposed to 13% from those with no IFTC protocol (P = .04). Respondents from hospitals with IFTC protocols reported significantly fewer barriers to communication compared to those without (2.8 vs 4.3; P = .03). Overall, however, most respondents (56%) reported a lack of standardization in communication. Presence of an IFTC protocol did not affect whether respondents perceived IFTC protocols as having a significant impact on infection prevention or antimicrobial stewardship.

Most respondents reported having an IFTC protocol, which was associated with reduced communication barriers at transfer. Standardization of protocols and clarity about expectations for sending and receipt of information related to MDRO status may facilitate IFTC and promote appropriate and timely infection prevention practices.

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.