National Healthcare Safety Network Definitions Research Articles

Pediatric cardiac surgical site infections: A single-center quality improvement initiative

ObjectivePediatric cardiac surgery site infections (SSI) represent significant morbidity. Our institution reported elevated SSI rates of 3.48 per 100 cases over a 5-year period above target rates of 2.5 per 100 cases. Therefore, as a quality improvement initiative, we implemented interventions with the goal of decreasing SSI rates by 30%. MethodsPediatric cardiovascular surgery patients (January 2021 to August 2023) who had SSI within 30 days of index operation were included (n = 1514) based on the National Healthcare Safety Network definition. Descriptive statistics were used to compare our preintervention cohort (pre-IV) (January 2021 to April 2022; n = 753) and postintervention cohort (post-IV) (May 2022 to August 2023; n = 761). ResultsIn the post-IV cohort, we found a significant decrease in total SSI (1.97 SSIs per 100 cases [15 out of 761]) versus pre-IV (3.85 SSIs per 100 cases [29 out of 753]), demonstrating a 48% reduction (P = .029). In our post-IV cohort, there was a significant reduction in superficial SSIs (pre-IV, 3.19 SSIs per 100 cases [24 out of 753] vs post-IV, 1.58 SSIs out of 100 cases [12 out of 761]; P = .04). Wounds presenting at 1 to 3 weeks were also reduced in our post-IV cohort (pre-IV, 2.66 SSIs per100 cases [20 out of 753] vs post-IV, 0.66 SSIs per 100 cases [5 out of 761]; P = .002). A significant reduction in SSIs in nonneonates was also noted (pre-IV, 2.79 SSIs per 100 cases [21 out of 753] vs post-IV, 0.92 SSIs per 100 cases [7 out of 761]; P = .007). Additionally, there was a significant reduction in SSIs associated with the Society of Thoracic Surgeons–European Association for Cardio-Thoracic Surgery Congenital Heart Surgery 1 mortality category (P = .033) and the number of readmissions in the post-IV cohort (P = .042). ConclusionsA new surgical site dressing and multidisciplinary surveillance plan effectively reduced the overall burden of SSI rates at our institution. Future studies will address risk factors in specific subpopulations to further reduce SSIs at our institution.

Positive predictive value of administrative diagnosis codes, for all patient encounters in the electronic health record, to detect postoperative infections: Retrospective cohort study after cesarean delivery

BackgroundPrioritization of anesthetizing locations for infection prevention depends on having a high positive predictive value for the detection of postoperative infection (PPV). Our study goal was to estimate the PPV after cesarean birth using hospital's International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes. Because earlier studies had low PPV for infection from antibiotic medication administration records, if each prescription had a corresponding diagnosis code, infections must have been listed for presumptive diagnoses (e.g., redness), not literally infection. Our cohort of obstetrical patients was unique for scientific investigation in that the vast majority developing postoperative infection were evaluated postoperatively by the same (surgical) department. MethodsThe population studied were all patients undergoing cesarean delivery from October 2015 through March 2022 at the University of Iowa. The ICD-10-CM codes were obtained from any type of encounter in the health record (e.g., clinic visit or emergency room). The hospital's quality improvement daily surveillance program followed National Healthcare Safety Network (NHSN) definitions. ResultsThe 147 cases studied were 2.9 % of the 5006 cesarean deliveries performed. Every postoperative infection from the daily surveillance program was included among the 147 cases. There were 144 of these patients evaluated by an obstetrician on the date of the ICD-10 diagnosis code(s) detecting postoperative infection. The estimated positive predictive value was 99.3 % (143/144), lower 95 % confidence limit 96.8 %. ConclusionsTo optimize patient benefit and hospital return on investment, infection preventive measures should include operating room/specialty combinations with the most postoperative infections. Automated health record review is needed. Every ICD-10-CM code is based on a clinician's note and thus the clinician's specialty (department) is known from the hospital's diagnosis tables. Using diagnosis codes for 90-day postoperative infection from surgeons' notes, high positive predictive value can be obtained (e.g., for use by anesthesia departments).

Burden of Healthcare-Associated Infections in a Pediatric Intensive Care Setting Before, During, and After the Pandemic

Background: Adult rates of non-COVID-19-related healthcare-associated infection (HAI) initially decreased and subsequently increased during the COVID-19 pandemic. Little is known about pediatric HAI rates during this period. Methods: A retrospective review of HAIs was conducted for patients admitted to the intensive care unit (PICU) at a pediatric tertiary care hospital between January 1, 2019 and November 30, 2023. Patients who spent ≥48 hours in the PICU were included. Surgical site infections were excluded. Data were obtained from infection surveillance reports; each HAI was reviewed for validity and attribution based on National Healthcare Safety Network definitions. HAIs were grouped into 3 time periods: pre-pandemic (January 2019-February 2020), pandemic (March 2020- February 2022), and post-pandemic (March 2022-November 2023). Infection rate ratios were calculated for pre-pandemic and post-pandemic periods. Results: Among 2,959 PICU patients admitted during the study period, there were 60 HAI events (4.78 per 1,000 patient days). Rates generally remained steady throughout with slight increases and decreases between time periods (Table 1). There was no significant difference in CAUTI, CLABSI, or HAVRI rates noted in the PICU between pre-pandemic and post-pandemic periods despite a significantly higher device utilization ratio in the post-pandemic period for both urinary catheters and central lines (IRR, 0.89; p < 0 .05; 95% CI, 0.82-0.97). The most frequent HAI in all time periods was CAUTI. Conclusion: Unlike reports from adult centers, no significant variation between time periods was noted for HAIs in our pediatric center. Despite numerous COVID-19-related changes in infection prevention and control measures and contexts throughout the study period, HAI rates remained stable. This may be due in part to the lower burden of critically ill COVID-19 pediatric patients compared to adult populations. Additionally, this could indicate resiliency and consistency in practice among pediatric providers throughout the pandemic. Further evaluation of pediatric HAIs in the context of the COVID-19 pandemic may reveal practices that could be replicated elsewhere to control HAI rates.

Factors Associated with Inappropriate Urine Culture Orders in Hospitalized Patients with Indwelling Urinary Catheters

Background: Catheter-associated urinary tract infection (CAUTI) is among the most prevalent healthcare-associated infections. Clinical diagnosis of CAUTI and National Healthcare Safety Network (NHSN) definitions do not always align. Most patients with indwelling urinary catheters ultimately develop asymptomatic bacteriuria (ASB) due to bacterial colonization and may be misattributed as CAUTI. Urine cultures ordered on patients with ASB may lead to reporting of non-clinically significant CAUTI to NHSN. We sought to examine factors associated with ordering inappropriate urine cultures in patients with urinary catheters. Methods: All CAUTIs that were reported to the NHSN at a large academic medical center in Eastern North Carolina were evaluated from October 2021-July 2023. A logistic regression model was fit for patients treated for urinary tract infection (UTI) with the following covariates: age, sex, time of urine culture order, provider type, and days that the urinary catheter was in place. All data analysis was performed in SAS (SAS Institute Inc., SAS 9.4, Cary, NC: SAS Institute Inc., 2002-2023). Results: Table 1 demonstrates patient characteristics stratified by treatment for UTI. The analysis suggests that abnormalresults from urine cultures ordered overnight were less likely to be treated with antibiotics,and this result was statistically significant in both the adjusted and unadjusted analyses – see table 2 and 3. The model also suggests abnormal results from urine cultures ordered by housestaff and older patients were more likely to be treated for UTI, but these results were not statistically significant – see table 3. Finally, the longer a catheter was in place the less likely an abnormalurine culture was to be treated and this finding was statistically significant – see table 3. Conclusion: Cultures that did not prompt antimicrobial treatment did not impact patient care decisions and could be considered as inappropriate orders. This can result in CAUTIs reported to NHSN that were not clinically significant. Abnormal results from cultures that were ordered by the overnight team were less likely to be treated for clinical UTI and this may represent an important target for diagnostic stewardship interventions.

Association of antibiotic duration and all-cause mortality in a prospective study of patients with ventilator-associated pneumonia in a tertiary-level critical care unit in Southern India

ObjectivesTo estimate all-cause mortality in ventilator-associated pneumonia (VAP) and determine whether antibiotic duration beyond 8 days is associated with reduction in all-cause mortality in patients admitted with VAP in the...

Hospital-acquired infections surveillance: The machine-learning algorithm mirrors National Healthcare Safety Network definitions.

Surveillance of hospital-acquired infections (HAIs) is the foundation of infection control. Machine learning (ML) has been demonstrated to be a valuable tool for HAI surveillance. We compared manual surveillance with a supervised, semiautomated, ML method, and we explored the types of infection and features of importance depicted by the model. From July 2021 to December 2021, a semiautomated surveillance method based on the ML random forest algorithm, was implemented in a Brazilian hospital. Inpatient records were independently manually searched by the local team, and a panel of independent experts reviewed the ML semiautomated results for confirmation of HAI. Among 6,296 patients, manual surveillance classified 183 HAI cases (2.9%), and a semiautomated method found 299 HAI cases (4.7%). The semiautomated method added 77 respiratory infections, which comprised 93.9% of the additional HAIs. The ML model considered 447 features for HAI classification. Among them, 148 features (33.1%) were related to infection signs and symptoms; 101 (22.6%) were related to patient severity status, 51 features (11.4%) were related to bacterial laboratory results; 40 features (8.9%) were related to invasive procedures; 34 (7.6%) were related to antibiotic use; and 31 features (6.9%) were related to patient comorbidities. Among these 447 features, 229 (51.2%) were similar to those proposed by NHSN as criteria for HAI classification. The ML algorithm, which included most NHSN criteria and >200 features, augmented the human capacity for HAI classification. Well-documented algorithm performances may facilitate the incorporation of AI tools in clinical or epidemiological practice and overcome the drawbacks of traditional HAI surveillance.

Surveillance of device associated infections in intensive care units at a Saudi Arabian Hospital, 2017–2020

BackgroundDevice-associated infections (DAIs) are important components of healthcare associated infection and are associated with increased morbidity and mortality. This study describes DAIs across different intensive care units (ICUs) in a hospital in Saudi Arabia. MethodsThe study was conducted between 2017 and 2020 and followed the definitions of National Healthcare Safety Network (NHSN) for DAIs. The calculated the rates of ventilator-associated events (VAE), catheter-associated urinary tract infections (CAUTI) and central line-associated blood stream infections (CLABSI) followed NHSN definitions. ResultsDuring the study period, there were 82 DAIs in adult ICUs and of these 16 (19.5%) were CLABSI, 26 (31.7%) were CAUTI and 40 (48.7%) were VAE. The overall rates for adult ICUs were 1.6, 1.9, 3.8 per 1000 device-days for CAUTI, CLABSI and VAE, respectively. The device-utilization ratio was 0.5, 0.6, and 0.48 for urinary catheters, central lines, and ventilators, respectively. VAE rates for medical and surgical ICU were about 2.8 times the rate in the coronary care unit and the rates were high in 2020 corresponding with the COVID-19 pandemic. Of the adult ICUS, medical ICU had a CLABSI rate of 2.13/1000 device-days and was about double the rate in surgical and cardiac ICU. For CAUTI, the rates per 1000 device-days were 2.19, 1.73, and 1.65 for medical, surgical, and coronary ICUs, respectively. The rate of CLABSI per 1000 device-days for pediatric and neonatal ICUs were 3.38 and 2.28, respectively. ConclusionsCAUTI was the most common infections among adult ICUs and medical ICU had higher rates than other adult ICUs. VAE rate was higher in the first year of the COVID-19 pandemic, indicating increased device-use, change in patients characteristics as well as possible change in practices across the ICUs.

Sensitivity of National Healthcare Safety Network definitions to capture healthcare-associated transmission identified by whole-genome sequencing surveillance.

The National Healthcare Safety Network (NHSN) definitions are critical for standardizing healthcare-associated infection surveillance in US healthcare facilities. However, their use in accurately detecting healthcare-associated transmission (HAT) has not been measured. Using whole-genome sequencing surveillance data, we show that the NHSN has a sensitivity of 44.4% in detecting HAT.

1204. Catheter-Associated Urinary Tract Infections (CAUTIs) and Secondary Hospital-Onset Bloodstream Infections (HO-BSIs)… Only the Tip of the Iceberg?

Abstract Background HO-BSIs – secondary to urinary tract infections (UTIs) – can result in substantial morbidity and mortality. The Centers for Disease Control and Prevention report that CAUTIs are the leading cause of secondary BSIs. However, more than 70% of hospital-onset UTIs (HO-UTIs) may be non-device associated. If that is the case, are a substantial number of HO-BSIs caused by non-CAUTI HO-UTIs? Methods A retrospective cohort analysis of nosocomial infections from 37 US hospitals was conducted using de-identified, real-world data from an electronic infection surveillance system. The analytic cohort included adults ≥ 18 years, without an infection diagnosis, and hospital length of stay ≥ 2 days, between October 2015 and June 2019. HO-UTI subjects presented with a non-contaminated positive urine culture on day 3 or later. Clinically meaningful HO-UTIs, were those with antimicrobials ordered ±2 days of the positive urine culture. CAUTI was defined per the National Healthcare Safety Network definition. Non-CAUTI HO-UTI were HO-UTIs not meeting the CAUTI definition. Secondary HO-BSIs were defined as non-contaminated, positive blood cultures occurring 2 days before or 4 days after the positive urine specimen, requiring an antimicrobial susceptibility test, and presenting with the same pathogen. Results Of the 568,293 inpatient admissions, 465,246 met the inclusion criteria. The vast majority of CAUTIs (401 of 436; 92%) and 75% of non-CAUTI HO-UTIs (3,256 of 4,374) were clinically meaningful. The relative burden of secondary HO-BSI was greater in patients with CAUTI (8%) compared to non-CAUTI HO-UTI (3%). However, the absolute risk of secondary HO-BSI was 3-times greater in non-CAUTI HO-UTI compared to CAUTI (96 cases vs 32 cases, respectively). 56% of secondary HO-BSI in CAUTI, and only 31% of secondary HO-BSI in non-CAUTI HO-UTI, likely originated in the intensive care unit (ICU). Case Tree Frequency of CAUTI and non-CAUTI HO-UTI. Frequency of secondary HO-BSI. Location of HO-UTI. Conclusion This retrospective, observational study found clinically meaningful non-CAUTI HO-UTIs to be 10-fold higher than the number of CAUTIs. In addition, the absolute burden of secondary HO-BSI is substantially higher in these non-CAUTI HO-UTIs and more likely to be associated with the non-ICU setting. The data suggests that evaluating CAUTI alone may underestimate the true burden of clinically meaningful HO-UTI. Disclosures ChinEn Ai, MPH, BD - Becton, Dickinson and Company: Employee|BD - Becton, Dickinson and Company: Stocks/Bonds Molly Jung, MPH, BD - Becton, Dickinson and Company: Employee|BD - Becton, Dickinson and Company: Stocks/Bonds Timothy Kelly, MS, MBA, BD - Becton, Dickinson and Company: Employee|BD - Becton, Dickinson and Company: Stocks/Bonds Kalvin Yu, MD, FIDSA, Becton, Dickinson and Company: Employee of, and shareholder in, Becton, Dickinson and Company, and the company received funding from GlaxoSmithKline plc. to conduct this study|GlaxoSmithKline plc.: GlaxoSmithKline plc.-sponsored study 212502.

Creation of a Novel Approach to Surveillance Through a Consolidated Abstraction Service

<h3>Background</h3> Abstraction for surveillance purposes is time consuming and can interrupt other duties required of infection preventionists (IP). While contracted services exist, they come at a cost and provide little ancillary value to an organization. Thus, we chose to create a consolidated abstraction service within our healthcare system with the goal of ensuring quality data through standardized application of National Healthcare Safety Network (NHSN) definitions and reducing variance through improved connection and collaboration. <h3>Methods</h3> The Clinical Data Registry Abstraction (CDRA) program was initiated in January 2020 as a shared service model, with 29 level 1 abstractors and 44 level 2 abstractors, plus a leadership team. Skill levels varied from no experience to extensive experience and Certified Infection Control (CIC) certification. The program included an intensive 8-week training program, monthly education seminars, and validation reviews with feedback for improvement. Communications channels were established for sharing best practices. The program covers 185 acute care facilities associated other sites of care across the United States. Abstractors use an electronic surveillance system to review daily cultures and complete an infection document that is sent to the IP for final review prior to submission to NHSN. <h3>Results</h3> A survey (59% facility response rate) rated the program 4.13 out of 5 overall. The domains of responsiveness and knowledge base were rated high, and 81% of respondents indicated that they received 1 to 3 hours back in their day. Survey comments highlighted IP retention, increased collaboration, return on investment for facilities, and reduction of IP workload as benefits. Areas for improvement included improving timeliness, expanding the scope, further standardization of processes, and increasing opportunities for shared learning. <h3>Conclusions</h3> In total, the CDRA program is a successful consolidated abstraction service that adds value to facilities and the organization. Investment in similar programs provides a valid alternative to contracted abstraction services.

Morbidity, mortality, and emerging drug resistance in Device-associated infections (DAIs) in intensive care patients at a 1000-bedded tertiary care teaching hospital

BackgroundDevice-associated infections (DAIs) such as ventilator associated pneumonia (VAP), central line–associated blood stream infection (CLABSI), and catheter-related urinary tract infection (CAUTI) are principal contributors to health hazard and a major preventable threat to patient safety. Robust surveillance of DAI delineates infections, pathogens, resistograms, and facilitates antimicrobial therapy, infection-control, antimicrobial stewardship, and improvement in quality of care. MethodsThis prospective outcome surveillance study was conducted amongst 2067 ICU patients in a 1000-bedded teaching hospital. Clinical, laboratory, and environmental surveillance, as well as screening of health care professionals (HCPs) were conducted using the modified US Centers for Disease Control and Prevention–National Healthcare Safety Network definitions and methods. Morbidity, mortality, and health-care indices were analyzed and two-tier infection prevention and control was promulgated. ResultsMean occupancy was 95.34% for 2061 patients of 7381 patients/bed/ICU days. One hundred seventeen episodes of DAI occurred in 1258 patients of 12,882 device-days with mean device utilization ratio of 1.79. Mean rate of DAI was 7.40 per 1000 device days. Multiresistant Pseudomonas aeruginosa was most commonly followed by Acinetobacter. Mean all-cause mortality in ICU was 24.85%, whereas all-cause mortality after DAI was 9.79%. Methicillin-resistant Staphylococcus aureus prevalence was 38.46% amongst health-care professionals. ConclusionMean rates of VAP, CLABSI, and CAUTI were 20.69, 2.53, and 2.23 per 1000 device days comparable with Indian and global ICUs. Resolute conviction and sustained momentum in infection prevention and control is an essential step toward patient safety.

Increased rates of secondary bacterial infections, including Enterococcus bacteremia, in patients hospitalized with coronavirus disease 2019 (COVID-19).

We compared the rates of hospital-onset secondary bacterial infections in patients with coronavirus disease 2019 (COVID-19) with rates in patients with influenza and controls, and we investigated reports of increased incidence of Enterococcus infections in patients with COVID-19. Retrospective cohort study. An academic quaternary-care hospital in San Francisco, California. Patients admitted between October 1, 2019, and October 1, 2020, with a positive SARS-CoV-2 PCR (N = 314) or influenza PCR (N = 82) within 2 weeks of admission were compared with inpatients without positive SARS-CoV-2 or influenza tests during the study period (N = 14,332). National Healthcare Safety Network definitions were used to identify infection-related ventilator-associated complications (IVACs), probable ventilator-associated pneumonia (PVAP), bloodstream infections (BSIs), and catheter-associated urinary tract infections (CAUTIs). A multiple logistic regression model was used to control for likely confounders. COVID-19 patients had significantly higher rates of IVAC and PVAP compared to controls, with adjusted odds ratios of 4.7 (95% confidence interval [CI], 1.7-13.9) and 10.4 (95 % CI, 2.1-52.1), respectively. COVID-19 patients had higher incidence of BSI due to Enterococcus but not BSI generally, and whole-genome sequencing of Enterococcus isolates demonstrated that nosocomial transmission did not explain the increased rate. Subanalyses of patients admitted to the intensive care unit and patients who required mechanical ventilation revealed similar findings. COVID-19 is associated with an increased risk of IVAC, PVAP, and Enterococcus BSI compared with hospitalized controls, which is not fully explained by factors such as immunosuppressive treatments and duration of mechanical ventilation. The mechanism underlying increased rates of Enterococcus BSI in COVID-19 patients requires further investigation.

Effect of Time of Daily Data Collection on the Calculation of Catheter-associated Urinary Tract Infection Rates.

Introduction:According to the National Healthcare Safety Network (NHSN) definitions for Catheter-associated urinary tract infections (CAUTI) rates, determination of the number of urinary catheter days must occur by calculating the number of catheters in place “for each day of the month, at the same time of day” but does not define at what time of day this occurs. The purpose of this review was to determine if a data collection time of 11 am would yield a greater collection of urinary catheter days than that done at midnight.Methods:During a 20-month period, the number of urinary catheter days was calculated using once-a-day electronic measurements to identify a urinary catheter presence. We used data collected at 11 am and collected at midnight (our historic default) in comparing the calculated urinary catheter days and resultant CAUTI rates.Results:There were 7,548 patients who had a urinary tract catheter. The number of urinary catheter days captured using the 11 am collection time was 15,425, and using the midnight collection time was 10,234, resulting in a 50.7% increase. The CAUTI rate per 1,000 urinary catheter days calculated using the 11 am collection method was 0.58, and using the midnight collection method was 0.88, a reduced CAUTI rate of 33.6%.Conclusion:The data collection time can significantly impact the calculation of urinary catheter days and on calculated CAUTI rates. Variations in how healthcare systems define their denominator per current National Healthcare Safety Network policy may result in significant differences in reported rates.

Automated Nationwide Benchmarking Dashboard for Antimicrobial Stewardship Programs within the Veterans’ Health Administration

Group Name: VHA Center for Antimicrobial Stewardship and Prevention of Antimicrobial Resistance (CASPAR) Background: Antimicrobial stewardship programs (ASPs) are advised to measure antimicrobial consumption as a metric for audit and feedback. However, most ASPs lack the tools necessary for appropriate risk adjustment and standardized data collection, which are critical for peer-program benchmarking. We created a system that automatically extracts antimicrobial use data and patient-level factors for risk-adjustment and a dashboard to present risk-adjusted benchmarking metrics for ASP within the Veterans’ Health Administration (VHA). Methods: We built a system to extract patient-level data for antimicrobial use, procedures, demographics, and comorbidities for acute inpatient and long-term care units at all VHA hospitals utilizing the VHA’s Corporate Data Warehouse (CDW). We built baseline negative binomial regression models to perform risk-adjustments based on patient- and unit-level factors using records dated between October 2016 and September 2018. These models were then leveraged both retrospectively and prospectively to calculate observed-to-expected ratios of antimicrobial use for each hospital and for specific units within each hospital. Data transformation and applications of risk-adjustment models were automatically performed within the CDW database server, followed by monthly scheduled data transfer from the CDW to the Microsoft Power BI server for interactive data visualization. Frontline antimicrobial stewards at 10 VHA hospitals participated in the project as pilot users. Results: Separate baseline risk-adjustment models to predict days of therapy (DOT) for all antibacterial agents were created for acute-care and long-term care units based on 15,941,972 patient days and 3,011,788 DOT between October 2016 and September 2018 at 134 VHA hospitals. Risk adjustment models include month, unit types (eg, intensive care unit [ICU] vs non-ICU for acute care), specialty, age, gender, comorbidities (50 and 30 factors for acute care and long-term care, respectively), and preceding procedures (45 and 24 procedures for acute care and long-term care, respectively). We created additional models for each antimicrobial category based on National Healthcare Safety Network definitions. For each hospital, risk-adjusted benchmarking metrics and a monthly ranking within the VHA system were visualized and presented to end users through the dashboard (an example screenshot in Figure 1). Conclusions: Developing an automated surveillance system for antimicrobial consumption and risk-adjustment benchmarking using an electronic medical record data warehouse is feasible and can potentially provide valuable tools for ASPs, especially at hospitals with no or limited local informatics expertise. Future efforts will evaluate the effectiveness of dashboards in these settings.Funding: NoDisclosures: None

Clinical Characteristics and Resistance Patterns of Pseudomonas aeruginosa Isolated From Combat Casualties.

Multidrug-resistant (MDR) Gram-negative infections complicate care of combat casualties. We describe the clinical characteristics, resistance patterns, and outcomes of Pseudomonas aeruginosa infections in combat casualties. Combat casualties included in the Trauma Infectious Disease Outcomes Study with infections with and without P. aeruginosa isolation during initial hospitalization were compared. Pseudomonas aeruginosa from initial wound, blood, and serial isolates (≥7 days from previous isolate) collected from June 2009 through February 2014 was subjected to antimicrobial susceptibility testing, pulsed-field gel electrophoresis, and whole genome sequencing for assessing clonality. Multidrug resistance was determined using the CDC National Healthcare Safety Network definition. Of 829 combat casualties with infections diagnosed during initial hospitalization, 143 (17%) had P. aeruginosa isolated. Those with P. aeruginosa were more severely injured (median Injury Severity Score 33 [interquartile range (IQR) 27-45] vs 30 [IQR 18.5-42]; P < .001), had longer hospitalizations (median 58.5 [IQR 43-95] vs 38 [IQR 26-56] days; P < .001), and higher mortality (6.9% vs 1.5%; P < .001) than those with other organisms. Thirty-nine patients had serial P. aeruginosa isolation (median 2 subsequent isolates; IQR: 1-5), with decreasing antimicrobial susceptibility. Ten percent of P. aeruginosa isolates were MDR, associated with prior exposure to antipseudomonal antibiotics (P = .002), with amikacin and colistin remaining the most effective antimicrobials. Novel antimicrobials targeting MDR Gram-negative organisms were also examined, and 100% of the MDR P. aeruginosa isolates were resistant to imipenem/relabactam, while ceftazidime/avibactam and ceftolozane/tazobactam were active against 35% and 56% of the isolates, respectively. We identified two previously unrecognized P. aeruginosa outbreaks involving 13 patients. Pseudomonas aeruginosa continues to be a major cause of morbidity, affecting severely injured combat casualties, with emergent antimicrobial resistance upon serial isolation. Among MDR P. aeruginosa, active antimicrobials remain the oldest and most toxic. Despite ongoing efforts, outbreaks are still noted, reinforcing the crucial role of antimicrobial stewardship and infection control.

Elimination of hospital‐acquired central line–associated bloodstream infection on a mixed‐service pediatric unit

Hospital-acquired central line-associated bloodstream infections (CLABSI) are "never events" in U.S. healthcare. National efforts to improve CLABSI rates are ongoing. Efforts are important for all patients with a central venous catheter (CVC) and critical to children with intestinal failure (IF) who depend on long-term, daily use of a CVC and undergo extended hospitalizations. We describe outcomes of a multidisciplinary CLABSI elimination effort on a 24-bed medical-surgical unit caring for children with IF. Unit CLABSI events from 1/9/2012 to 4/16/2020 were evaluated with multiple improvement interventions. We leveraged prospectively maintained clinical registries and National Healthcare Safety Network (NHSN) reporting data to extract patient and unit demographics, ethanol lock utilization, and unit CVC days. Interventions were developed utilizing expert consensus and CDC guidelines with active frontline staff engagement. Descriptive statistics and tests of non-parametric data were employed for analysis. Ninety-five patients with IF and 862 non-IF patients experienced a total of 1,629 admissions with 20,372 CVC days. Twelve hospital-acquired CLABSI events occurred during the study period, including 7 following NHSN definition change on 1/1/2015 (0.56 per 1,000 CVC days). After the last unit CLABSI on 12/5/2016, there were 7,117 CVC days through study conclusion. Described interventions with an enhanced culture of collaborative care profoundly improved hospital-acquired CLABSI occurrence. Success in a specific population translated to all other unit patients with a CVC. Findings suggest elimination is not the result of a single new product or practice, but also includes support and empowerment of those caring for the patient and their CVC.

Development of a Community-onset Clostridioides difficile Detection Tool to Prevent Delayed Identification of Infection

<h3>Background</h3> : Clostridioides difficile (Cdiff) identified after hospital day (HD) three are classified as hospital-onset (HO) while those identified prior are community-onset (CO) based on National Healthcare Safety Network definitions. At a Level 1 Trauma Center it was determined that a portion of HO Cdiff cases were likely CO with delayed identification. The objective was to develop an early detection tool to aid in earlier testing of high-risk patients with CO Cdiff. <h3>Methods</h3> : A report was developed to identify a list of patients admitted in previous two days with≥ one loose stool and potential Cdiff risk factors including: number of liquid stools, white blood cell count, temperature, antibiotic exposure, diarrhea at home, and transfer source. Risk factors were weighted, resulting in a daily CO Cdiff risk index for each patient ranging from -2 to +10. Patient with a risk index ≥+1 was escalated to nursing leadership for evaluation and testing. <h3>Results</h3> : Between January 2019 and August 2020, 25% (n = 10) of HO Cdiff cases were identified on HD four through six. In the first two months of report implementation (September - October 2020), 354 patients were admitted with ≥ one loose stool in the first three HD. Over 25% (n = 93) of these patients were given a risk index of ≥+1 and testing were recommended. Testing was performed on 26 patients (28.0%) which resulted in identification of 10 (38.5%) CO Cdiff cases. Reasons for not testing included: patient discharged (n = 14), loose stool ceased (n = 20), did not meet criteria (n = 8), death (n = 1) and no follow up (n = 20). In this time period, no cases of Cdiff were identified between HD four and six. <h3>Conclusions</h3> : Early identification of CO Cdiff has multiple benefits including early isolation, appropriate treatment and reduction of misclassification of HO events.

Factors Related to the Accurate Application of NHSN Surveillance Definitions for CAUTI and CLABSI in Texas Hospitals

Background Previous studies indicate inconsistent knowledge and application of the National Healthcare Safety Network (NHSN) surveillance definitions used to report Healthcare Associated Infections (HAI). Our study aims to determine factors associated with accurate application of the surveillance criteria. Methods Members of Texas Infection Prevention (IP) professional organizations were emailed a web-based survey in January 2020. Respondents answered demographic and other questions related to 2019 NHSN trainings completed and applied NHSN definitions to case scenarios on Catheter-Associated Urinary Tract Infection (CAUTI) and Central Line-Associated Bloodstream Infection (CLABSI). This cross-sectional study used logistic regression models to estimate associations between years of experience, hours spent on surveillance, NHSN trainings, and respondents’ ability to identify correct HAI criterion. Results Eighty-eight IPs responded to the survey. Twenty-five of 65 respondents (38%) who completed CAUTI training identified correct CAUTI criterion and 6 of 63 (10%) who completed CLABSI training identified correct CLABSI criterion. CAUTI training was associated with higher odds of accurately identifying CAUTI (Odds Ratio (OR) = 4.92, 95% Confidence Interval (CI): 1.2, 20.5) after adjusting for years of experience and hours spent on surveillance. Similar patterns of association were observed between completion of CLABSI training and correctly identifying CLABSI, but the result was not significant (OR = 2.35, 95% CI: 0.2, 23.8). Compared to those spending less time on NHSN surveillance ( 16 hours/week) had lower odds of identifying CAUTI but higher odds of identifying CLABSI. Conclusions Limited studies demonstrate variability in the accurate application of NHSN surveillance definitions. Possible factors contributing to this variability are also lacking. Our results suggest that recent NHSN training and more years of IP experience may be associated with increased accuracy of HAI identification. However, spending more time with NHSN surveillance every week may not improve one's ability to identify CAUTI.

Is antibiotic prophylaxis expendable in parotid gland surgery? A retrospective analysis of surgical site infection rates.

To evaluate the rate of surgical site infection (SSI) and associated risk factors after parotid gland surgery including the impact of antibiotic prophylaxis. Retrospective single-centre clinical study. Tertiary referral centre for head and neck surgery. Seven hundred and fifty four patients who underwent parotid gland surgery at the University Hospital Heidelberg, Germany, between 2007 and 2014 were enrolled in this study. Data on patient age, American Society of Anesthesiologists (ASA) classification system, smoking status, diabetes mellitus, operation time, and antibiotic prophylaxis were collected. Additionally, the National Healthcare Safety Network (NHSN) risk index was calculated. Association of these factors with SSI was evaluated in univariate analyses and a multivariate logistic regression model. Rate of SSI. Twenty four patients (3.2%) had an SSI according to the NHSN definition. In univariate analyses, only smokers (P=.048) and male patients (P=.01) had a significantly higher rate of SSI. Since the majority of smokers were men (62.3%), the effect of male gender, smoking, together with the NHSN risk index was further investigated as predictors of SSI within a logistic regression model. All three predictors showed a significant effect on SSI. Parotid gland surgery has a low rate of SSI. In our cohort, male gender, smoking and high NHSN risk index scores were significantly associated with SSI, whereas antibiotic prophylaxis had no protective effect.

The Epidemiology of Meningitis in Infants under 90 Days of Age in a Large Pediatric Hospital.

Background: Meningitis is associated with substantial morbidity and mortality, particularly in the first three months of life. Methods: We conducted a retrospective review of patients <90 days of age with meningitis at Texas Children’s Hospital from 2010–2017. Cases were confirmed using the National Healthcare Safety Network (NHSN) definition of meningitis. Results: Among 694 infants with meningitis, the most common etiology was viral (n = 351; 51%), primarily caused by enterovirus (n = 332; 95%). A quarter of cases were caused by bacterial infections (n = 190; 27%). The most common cause of bacterial meningitis was group B Streptococcus (GBS, n = 60; 32%), followed by Gram-negative rods other than E. coli (n = 40; 21%), and E. coli (n = 37; 19%). The majority of Gram-negative organisms (63%) were resistant to ampicillin, and nearly one-fourth of Gram-negative rods (23%) other than E. coli and 2 (6%) E. coli isolates were resistant to third-generation cephalosporins. Significant risk factors for bacterial meningitis were early preterm birth and the Black race. Conclusions: Enteroviruses most commonly caused viral meningitis in infants; GBS was the most common bacterial cause despite universal screening and intrapartum prophylaxis. The emergence of MRSA and resistance to third-generation cephalosporins in Gram-negative bacterial meningitis challenges the options for empirical antimicrobial therapy.