scholarly journals Building an Interactive Geospatial Visualization Application for National Healthcare-Associated Infection Surveillance (Preprint)

2020 ◽  
Author(s):  
Shuai Zheng ◽  
Jonathan R. Edwards ◽  
Margaret A. Dudeck ◽  
Prachi Patel ◽  
Lauren Wattenmaker ◽  
...  
Keyword(s):  
Quality Measurement ◽  
Healthcare Facility ◽  
The United States ◽  
Surveillance Program ◽  
Development Effort ◽  
Healthcare Associated Infection ◽  
Healthcare Facilities ◽  
National Healthcare ◽  
State And Local ◽  
Healthcare Associated

BACKGROUND The Centers for Disease Control and Prevention’s (CDC’s) National Healthcare Safety Network (NHSN) is the most widely used healthcare-associated infection (HAI) and antimicrobial use and resistance (AUR) surveillance program in the United States. Over 37,000 healthcare facilities participate in the program and submit a large volume of HAI and AUR surveillance data. These data are used by the facilities themselves, CDC, and other agencies and organizations for a variety of purposes, including infection prevention, antimicrobial stewardship, and clinical quality measurement. Among the summary metrics made available by NHSN are standardized infection ratios (SIRs), which are used to identify HAI prevention needs and measure progress at the national, regional, state and local levels. OBJECTIVE To extend the use of geospatial methods and tools to NHSN data, and in turn to promote and inspire new uses of the rendered data for analysis and prevention purposes, we developed a web-enabled system that enables integrated visualization of HAI metrics and supporting data. METHODS We leveraged geocoding and visualization technologies that are readily available and in current use to develop a web-enabled system designed to support visualization and interpretation of data submitted to NHSN from geographically dispersed sites. The server-client model-based system enables users to access the application via a web-browser. RESULTS We integrated multiple datasets into a single page dashboard designed to enable users to navigate across different HAI event types, choose specific healthcare facility or geographic locations for data displays, and scale across time units within identified time periods. We launched the system for internal CDC use in January 2019. CONCLUSIONS CDC NHSN statisticians, data analysts, and subject matter experts identified opportunities to extend the use of geospatial methods and tools to NHSN data and provided the impetus to develop NHSNViz. The development effort proceeded iteratively, with the developer adding or enhancing functionality and including additional data sets in a series of prototype versions, each of which incorporated user feedback. The initial production version of NHSNViz provides a new geospatial analytic resource built in accordance with CDC user requirements and extensible to additional users and uses in subsequent versions.

scholarly journals Assessing The Impact of The National Healthcare Safety Network’s (NHSN’s) New Baseline on Acute Care Hospital Standardized Infection Ratios (SIRs)

2017 ◽  
Vol 4 (suppl_1) ◽  
pp. S49-S50
Author(s):  
Minn Soe ◽  
Allan Nkwata ◽  
Jonathan R Edwards ◽  
Margaret Dudeck ◽  
Daniel Pollock
Keyword(s):  
Acute Care ◽  
Risk Adjustment ◽  
Acute Care Hospital ◽  
Healthcare Facility ◽  
Care Hospital ◽  
Healthcare Associated Infection ◽  
Quality Reporting ◽  
National Healthcare ◽  
Healthcare Associated ◽  
The Impact

Abstract Background To more accurately measure the progress of healthcare-associated infection (HAI) prevention efforts, the CDC’s National Healthcare Safety Network (NHSN) surveillance system updated risk-adjustment models for computation of updated Standardized Infection Ratios (SIRs), the primary HAI summary measure by NHSN. This study sought to examine how the updated SIRs varied from the previous SIRs calculated using older baselines for acute care hospital HAIs. Methods We analyzed NHSN data for healthcare facility-onset laboratory-identified Clostridium difficile [CDI] and methicillin-resistant Staphylococcus aureus [MRSA] bacteremia reported in accordance with the CMS’ inpatient quality reporting program requirement. The unit of analysis was CMS certification number (CCN) facility reporting in 2015. We compared overall distributions of CCN-level SIRs (CCN-SIRs) between new risk-adjustment models using a 2015 baseline (SIR_NEW) and old models using a 2011 baseline (SIR_OLD) and tested location shift (median away from null) of pairwise differences. We also examined the magnitude of shift in SIR from old to new baseline. Results For each HAI, the national pooled mean SIR of the new baseline was ~1.0. For CDI, the overall distributions of CCN SIR_NEW and CCN-SIR_OLD were different, and the median of pairwise difference was away from null with CCN-SIR_NEW slightly higher. For MRSA, the SIR differences were not significant. Most CCN-SIRs (83% for CDI, 93% for MRSA) remained in the same significance category across the old and new baselines (“worse,” “better, ‘not different from national benchmark’), and few CCN-SIRs were reclassified to a less favorable category. For 75% of CCN-SIRs, their relative position in the quartile distributions of SIR_NEW and SIR_OLD remained the same. The discrepancies between SIR_NEW and SIR_OLD tended to be larger among CCNs with high SIRs. Conclusion The updated national pooled mean SIRs were close to 1.0, validating the potential use of new risk adjustment models and baseline as updated benchmarks for tracking CDI and MRSA prevention progress. The shifts in CCN-level SIRs between old and new baselines were not large, indicating a modest impact of new baselines at the CCN level, except among hospitals with high SIRs. Disclosures All authors: No reported disclosures.

scholarly journals Evolution of Healthcare-Associated Infections and Antibiotic Resistance Programs in US Health Departments, 2009–2018

2020 ◽  
Vol 41 (S1) ◽  
pp. s232-s232
Author(s):  
Michael Ashley ◽  
Stephanie Gumbis ◽  
Jennifer C. Hunter ◽  
Joseph Perz
Keyword(s):  
Public Health ◽  
Antibiotic Resistance ◽  
Acute Care ◽  
Multidrug Resistant ◽  
Advisory Group ◽  
Healthcare Associated Infection ◽  
Healthcare Facilities ◽  
Response Capacity ◽  
State And Local ◽  
Healthcare Associated

Background: Domestically, the integration of public health into healthcare-associated infection (HAI) and antibiotic resistance (AR) prevention activities represents a major development. We describe CDC Funding: of public health HAI/AR programs through the Epidemiology and Laboratory Capacity (ELC) cooperative agreement to improve local capacity to prevent HAIs and detect and contain the spread of AR threats. Methods: We reviewed ELC budget reports and program documents to summarize the evolution of funded activities and programs from 2009 to 2018. Results: In 2009, 51 programs (49 states, 2 cities and territories) received US$35.8 million through the American Recovery and Reinvestment Act for an initial 28-month period. These funds supported each jurisdiction to establish an HAI coordinator and a multidisciplinary HAI advisory group, coordinate and report HAI prevention efforts, conduct surveillance and report HAI data, and maintain an HAI plan; ~27 programs were also funded to coordinate multicenter HAI prevention collaboratives among acute-care hospitals. Through 2011, 188 state or local HAI/AR program positions were at least partially funded by the CDC. From 2011 to 2015, investments from the Affordable Care Act (~US$10–11 million annually) were used to maintain the HAI/AR programs, with some expansion of program goals related to non–acute-care settings and antibiotic stewardship. In 2015, following the Ebola outbreak in West Africa, supplemental ELC funds were awarded to 61 programs (50 states, 11 cities and territories) totaling US$85 million over 36 months. These awards marked an expansion of HAI/AR program activities to develop healthcare provider inventories, to conduct data-driven education and training, and to perform onsite infection control assessments in healthcare facilities. In 2016, through its AR Solutions Initiative, CDC invested US$57.3 million in Funding: to 57 programs (50 states, 7 cities and territories), expanding laboratory capacities for AR threat detection (via the AR Laboratory Network) and epidemiologic activities to rapidly contain novel and targeted multidrug-resistant organisms. As of 2018, >500 state or local HAI/AR program positions were at least partially funded by the CDC. Conclusions: State and local HAI/AR programs have grown substantially over the 10 years of their existence, as reflected in major increases in funding, staffing, scope, and partnerships. CDC investments and guidance have supported the development of HAI/AR epidemiology prevention and response capacity.Funding: NoneDisclosures: None

scholarly journals Diminishing Surgical Site Infections in Australia: Time Trends in Infection Rates, Pathogens and Antimicrobial Resistance Using a Comprehensive Victorian Surveillance Program, 2002–2013

2015 ◽  
Vol 36 (4) ◽  
pp. 409-416 ◽  
Author(s):  
Leon J. Worth ◽  
Ann L. Bull ◽  
Tim Spelman ◽  
Judith Brett ◽  
Michael J. Richards
Keyword(s):  
Risk Reduction ◽  
Time Trends ◽  
Artery Bypass ◽  
Surgical Site Infections ◽  
Surveillance Program ◽  
Healthcare Associated Infection ◽  
Surveillance Strategy ◽  
Healthcare Facilities ◽  
Surgical Antibiotic Prophylaxis ◽  
Healthcare Associated

OBJECTIVETo evaluate time trends in surgical site infection (SSI) rates and SSI pathogens in Australia.DESIGNProspective multicenter observational cohort study.SETTINGA group of 81 Australian healthcare facilities participating in the Victorian Healthcare Associated Infection Surveillance System (VICNISS).PATIENTSAll patients underwent surgeries performed between October 1, 2002, and June 30, 2013. National Healthcare Safety Network SSI surveillance methods were employed by the infection prevention staff at the participating hospitals.INTERVENTIONProcedure-specific risk-adjusted SSI rates were calculated. Pathogen-specific and antimicrobial-resistant (AMR) infections were modeled using multilevel mixed-effects Poisson regression.RESULTSA total of 183,625 procedures were monitored, and 5,123 SSIs were reported. Each year of observation was associated with 11% risk reduction for superficial SSI (risk ratio [RR], 0.89; 95% confidence interval [CI], 0.88–0.90), 9% risk reduction for deep SSI (RR, 0.91; 95% CI, 0.90–0.93), and 5% risk reduction for organ/space SSI (RR, 0.95; 95% CI, 0.93–0.97). Overall, 3,318 microbiologically confirmed SSIs were reported. Of these SSIs, 1,174 (35.4%) were associated with orthopedic surgery, 827 (24.9%) with coronary artery bypass surgery, 490 (14.8%) with Caesarean sections, and 414 (12.5%) with colorectal procedures. Staphylococcus aureus was the most frequently identified pathogen, and a statistically significant increase in infections due to ceftriaxone-resistant Escherichia coli was observed (RR, 1.37; 95% CI, 1.10–1.70).CONCLUSIONSStandardized SSI surveillance methods have been implemented in Victoria, Australia. Over an 11-year period, diminishing rates of SSIs have been observed, although AMR infections increased significantly. Our findings facilitate the refinement of recommended surgical antibiotic prophylaxis regimens and highlight the need for a more expansive national surveillance strategy to identify changes in epidemiology.Infect Control Hosp Epidemiol 2015;00(0): 1–8

Managing Our Microbial Mark

2016 ◽  
Vol 42 (2-3) ◽  
pp. 393-428
Author(s):  
Ann Marie Marciarille
Keyword(s):  
United States ◽  
Infection Control ◽  
The United States ◽  
West African ◽  
Healthcare Associated Infections ◽  
Healthcare Facilities ◽  
Quality Reporting ◽  
Reporting Systems ◽  
Control Procedures ◽  
Healthcare Associated

The narrative of Ebola's arrival in the United States has been overwhelmed by our fear of a West African-style epidemic. The real story of Ebola's arrival is about our healthcare system's failure to identify, treat, and contain healthcare associated infections. Having long been willfully ignorant of the path of fatal infectious diseases through our healthcare facilities, this paper considers why our reimbursement and quality reporting systems made it easy for this to be so. West Africa's challenges in controlling Ebola resonate with our own struggles to standardize, centralize, and enforce infection control procedures in American healthcare facilities.

scholarly journals 2476. External and Internal Validation of the Healthcare-associated Infection Data in the Korean National Healthcare-associated Infectious Surveillance System (KONIS)

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S857-S858
Author(s):  
Yee Gyung Kwak ◽  
Je Eun Song ◽  
Young Hwa Choi ◽  
Sung Ran Kim ◽  
Su Ha Han ◽  
...  
Keyword(s):  
Surveillance System ◽  
Bloodstream Infections ◽  
Surveillance Data ◽  
Healthcare Associated Infection ◽  
Continuous Training ◽  
Monitoring Method ◽  
Internal Validation ◽  
National Healthcare ◽  
Tract Infections ◽  
Healthcare Associated

Abstract Background National surveillance data should be validated to identify data quality issues. This study tested the validity of healthcare-associated infection (HAI) data in the Korean National Healthcare-associated Infections Surveillance System (KONIS), intensive care unit (ICU) module. Methods The validation process consisted of external (EV) and internal (IV) validation phases. For the 10 hospitals that were selected based on the HAI rate, among the 193 participating hospitals between July 2016 and June 2017, both EV and IV were performed. For the EV, the validation team reviewed 295 medical records of 60 patients with reported HAIs, including 20 urinary tract infections (UTIs), 27 bloodstream infections (BSIs), and 13 cases of pneumonia (PNEU), and 235 patients with no reported HAI during 1-day visits conducted in November and December 2017. The reviewer’s diagnosis of HAI was regarded as the reference standard. IV was conducted by the staff of each hospital and evaluated whether UTI or BSI were present. Primary IV was performed for 279 patients who were subject to EV. Secondary IV was performed on 203 patients in another 11 selected participating hospitals that did not report HAIs to KONIS during the 1-year study period. Results In the EV, the diagnosis of UTI in the participating hospitals had a sensitivity of 72.0% and specificity of 99.3%. The sensitivity of BSI and PNEU was 63.2% and 70.6%, respectively, and specificity was 98.8% and 99.6%. The agreement (kappa) between the EV and primary IV was significant, with κ = 0.754 for UTI and κ = 0.674 for BSI. The results of the secondary IV showed that the hospitals that had no reports of HAI had few hospital beds and performed few blood or urine culture tests. In the secondary IV, eight UTIs and three BSIs were newly diagnosed in three hospitals, respectively. The reasons for not reporting the HAIs were presumed to be a lack of understanding of the surveillance standards and fear of the disadvantages of disclosing the HAI. Conclusion This study shows the need for ongoing validation and continuous training of surveillance personnel to maintain the accuracy of surveillance data. We also confirmed that IV can be used as an alternative monitoring method to examine validity and accuracy. Disclosures All authors: No reported disclosures.

scholarly journals Clinical Practice Guidelines for Clostridium difficile Infection in Adults and Children: 2017 Update by the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA)

2018 ◽  
Vol 66 (7) ◽  
pp. 987-994 ◽  
Author(s):  
L Clifford McDonald ◽  
Dale N Gerding ◽  
Stuart Johnson ◽  
Johan S Bakken ◽  
Karen C Carroll ◽  
...  
Keyword(s):  
United States ◽  
Clinical Practice ◽  
Clostridium Difficile ◽  
Infectious Diseases ◽  
Clostridium Difficile Infection ◽  
The United States ◽  
Healthcare Associated Infection ◽  
Adults And Children ◽  
Healthcare Associated ◽  
Healthcare Epidemiology

Abstract A panel of experts was convened by the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA) to update the 2010 clinical practice guideline on Clostridium difficile infection (CDI) in adults. The update, which has incorporated recommendations for children (following the adult recommendations for epidemiology, diagnosis, and treatment), includes significant changes in the management of this infection and reflects the evolving controversy over best methods for diagnosis. Clostridium difficile remains the most important cause of healthcare-associated diarrhea and has become the most commonly identified cause of healthcare-associated infection in adults in the United States. Moreover, C. difficile has established itself as an important community pathogen. Although the prevalence of the epidemic and virulent ribotype 027 strain has declined markedly along with overall CDI rates in parts of Europe, it remains one of the most commonly identified strains in the United States where it causes a sizable minority of CDIs, especially healthcare-associated CDIs. This guideline updates recommendations regarding epidemiology, diagnosis, treatment, infection prevention, and environmental management.

scholarly journals Defining the black box: a narrative review of factors associated with adverse outcomes from severe Clostridioides difficile infection

2021 ◽  
Vol 14 ◽  
pp. 175628482110481
Author(s):  
Adam Ressler ◽  
Joyce Wang ◽  
Krishna Rao
Keyword(s):  
The United States ◽  
Adverse Outcomes ◽  
Chronic Illnesses ◽  
Narrative Review ◽  
Healthcare Associated Infection ◽  
Clostridioides Difficile ◽  
Clostridioides Difficile Infection ◽  
Patients At Risk ◽  
Hospital Deaths ◽  
Healthcare Associated

In the United States, Clostridioides difficile infection (CDI) is the leading cause of healthcare-associated infection, affecting nearly half a million people and resulting in more than 20,000 in-hospital deaths every year. It is therefore imperative to better characterize the intricate interplay between C. difficile microbial factors, host immunologic signatures, and clinical features that are associated with adverse outcomes of severe CDI. In this narrative review, we discuss the implications of C. difficile genetics and virulence factors in the molecular epidemiology of CDI, and the utility of early biomarkers in predicting the clinical trajectory of patients at risk of developing severe CDI. Furthermore, we identify associations between host immune factors and CDI outcomes in both animal models and human studies. Next, we highlight clinical factors including renal dysfunction, aging, blood biomarkers, level of care, and chronic illnesses that can affect severe CDI diagnosis and outcome. Finally, we present our perspectives on two specific treatments pertinent to patient outcomes: metronidazole administration and surgery. Together, this review explores the various venues of CDI research and highlights the importance of integrating microbial, host, and clinical data to help clinicians make optimal treatment decisions based on accurate prediction of disease progression.

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