Keith F Woeltje

Washington University in St. Louis, San Luis, Missouri, United States

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Publications (38)152.94 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Objective. Central line-associated bloodstream infection (BSI) rates are a key quality metric for comparing hospital quality and safety. Traditional BSI surveillance may be limited by interrater variability. We assessed whether a computer-automated method of central line-associated BSI detection can improve the validity of surveillance. Design. Retrospective cohort study. Setting. Eight medical and surgical intensive care units (ICUs) in 4 academic medical centers. Methods. Traditional surveillance (by hospital staff) and computer algorithm surveillance were each compared against a retrospective audit review using a random sample of blood culture episodes during the period 2004-2007 from which an organism was recovered. Episode-level agreement with audit review was measured with κ statistics, and differences were assessed using the test of equal κ coefficients. Linear regression was used to assess the relationship between surveillance performance (κ) and surveillance-reported BSI rates (BSIs per 1,000 central line-days). Results. We evaluated 664 blood culture episodes. Agreement with audit review was significantly lower for traditional surveillance (κ [95% confidence interval [Formula: see text] [0.37-0.51]) than computer algorithm surveillance (κ [95% [Formula: see text] [0.52-0.64]; [Formula: see text]). Agreement between traditional surveillance and audit review was heterogeneous across ICUs ([Formula: see text]); furthermore, traditional surveillance performed worse among ICUs reporting lower (better) BSI rates ([Formula: see text]). In contrast, computer algorithm performance was consistent across ICUs and across the range of computer-reported central line-associated BSI rates. Conclusions. Compared with traditional surveillance of bloodstream infections, computer automated surveillance improves accuracy and reliability, making interfacility performance comparisons more valid.
    Infection Control and Hospital Epidemiology 12/2014; 35(12):1483-90. · 3.94 Impact Factor
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    ABSTRACT: Electronic surveillance for healthcare-associated infections (HAIs) is increasingly widespread. This is driven by multiple factors: a greater burden on hospitals to provide surveillance data to state and national agencies, financial pressures to be more efficient with HAI surveillance, the desire for more objective comparisons between healthcare facilities, and the increasing amount of patient data available electronically. Optimal implementation of electronic surveillance requires that specific information be available to the surveillance systems. This white paper reviews different approaches to electronic surveillance, discusses the specific data elements required for performing surveillance, and considers important issues of data validation.
    Infection Control and Hospital Epidemiology 09/2014; 35(9):1083-1091. · 3.94 Impact Factor
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    ABSTRACT: Venous thromboembolism (VTE) is the most common preventable cause of morbidity and mortality in the hospital. Adequate thromboprophylaxis has reduced the rate of hospital-acquired VTE substantially; however, some inpatients still develop VTE even when they are prescribed thromboprophylaxis. Predictors associated with thromboprophylaxis failure are unclear. In this study, we aimed to identify risk factors for inpatient VTE despite thromboprophylaxis. We conducted a case-control study to identify independent predictors for inpatient VTE. Among patients discharged from the BJC HealthCare system between January 2010 and May 2011, we matched 94 cases who developed in-hospital VTE while taking thromboprophylaxis to 272 controls who did not develop VTE. Matching was done by hospital, patient age, month and year of discharge. We used multivariate conditional logistic regression to develop a VTE prediction model. We identified five independent risk factors for in-hospital VTE despite thromboprophylaxis: hospitalization for cranial surgery, intensive care unit admission, admission leukocyte count >13,000/mm(3), presence of an indwelling central venous catheter, and admission from a long-term care facility. We identified five risk factors associated with the development of VTE despite thromboprophylaxis in the hospital setting. By recognizing these high-risk patients, clinicians can prescribe aggressive VTE prophylaxis judiciously and remain vigilant for signs or symptoms of VTE.
    Thrombosis Research 09/2013; · 2.43 Impact Factor
  • Keith F Woeltje, Hilary M Babcock
    Canadian Medical Association Journal 08/2013; 185(11):983-4. · 5.81 Impact Factor
  • Infection Control and Hospital Epidemiology 06/2013; 34(6):655-6. · 4.02 Impact Factor
  • American Journal of Infection Control 06/2013; 41(6):S51. · 2.33 Impact Factor
  • K F Woeltje
    The Journal of hospital infection 05/2013; · 3.01 Impact Factor
  • Infection Control and Hospital Epidemiology 09/2012; 33(9):952-4. · 4.02 Impact Factor
  • Source
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    ABSTRACT: Manual surveillance for central line-associated bloodstream infections (CLABSIs) by infection prevention practitioners is time-consuming and often limited to intensive care units (ICUs). An automated surveillance system using existing databases with patient-level variables and microbiology data was investigated. Patients with a positive blood culture in 4 non-ICU wards at Barnes-Jewish Hospital between July 1, 2005, and December 31, 2006, were evaluated. CLABSI determination for these patients was made via 2 sources; a manual chart review and an automated review from electronically available data. Agreement between these 2 sources was used to develop the best-fit electronic algorithm that used a set of rules to identify a CLABSI. Sensitivity, specificity, predictive values, and Pearson's correlation were calculated for the various rule sets, using manual chart review as the reference standard. During the study period, 391 positive blood cultures from 331 patients were evaluated. Eighty-five (22%) of these were confirmed to be CLABSI by manual chart review. The best-fit model included presence of a catheter, blood culture positive for known pathogen or blood culture with a common skin contaminant confirmed by a second positive culture and the presence of fever, and no positive cultures with the same organism from another sterile site. The best-performing rule set had an overall sensitivity of 95.2%, specificity of 97.5%, positive predictive value of 90%, and negative predictive value of 99.2% compared with intensive manual surveillance. Although CLABSIs were slightly overpredicted by electronic surveillance compared with manual chart review, the method offers the possibility of performing acceptably good surveillance in areas where resources do not allow for traditional manual surveillance.
    Infection Control and Hospital Epidemiology 11/2011; 32(11):1086-90. · 4.02 Impact Factor
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    ABSTRACT: Background: In 2009, BJC HealthCare committed to reducing their healthcare associated (HA-PrU) by 75% by 2012. Currently, we utilize standard pressure ulcer risk assessments, skin inspections and prevention efforts as part of quality management for patient care. Despite these efforts, we have not seen a sufficient decrease in our HA-PrU rate. To become better equipped to design and implement effective intervention strategies, we performed a patient level risk factor assessment. Objective: To assess and identify the patient level HA-PrU risk factors and use this information to develop intervention strategies. Methods: We utilized data from 3 hospitals to conduct a case-control study. We matched cases and controls 3 to 1 by hospital and age within 5 years. We analyzed data using descriptive statistics and binary analysis to identify actionable risk factors for intervention consideration. Regression modeling was also conducted to develop predictive models for pressure ulcers. Results: Our analysis found several significant risk factors for HA-PrU; BMI <18.5 (OR=4.1, p<0.05), mechanical ventilation (OR=6.4, p<0.001), edema (OR= 8.7, p<0.001), incontinence (OR= 3.9, p<0.001), surgery (OR= 3.89, p<0.001), and no food by mouth for three or more days (NPO) (OR= 5.4, p<0.001), renal insufficiency (OR=2.0, p<0.05), non-pressure ulcer skin lesions (OR=5.4, p<0.01) and at least one episode of low diastolic blood pressure (OR=18.3, p<0.01). Our best predictive model (R2=0.40) included edema, surgery, NPO, BMI and number of low diastolic blood pressure days. Conclusions: This information, in conjunction with current risk assessments, can be used to better identify patients at increased risk for pressure ulcers and the implementation of aggressive and early intervention. Utilizing this data, BJC HealthCare is examining modification of our current risk assessment processes, as well as evaluating and enhancing the pressure ulcer prevention strategies used in the operating room.
    139st APHA Annual Meeting and Exposition 2011; 11/2011
  • American Journal of Infection Control 06/2011; 39(5):E30–E31. · 2.33 Impact Factor
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    Keith F Woeltje, Ebbing Lautenbach
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    ABSTRACT: Increasing amounts of hospital data are available electronically and offer new possibilities in performing surveillance for health care-associated infections. To use electronic information effectively, health care epidemiologists need to be aware of potential sources of data, issues with data integrity, and the trade-offs in using electronic data for surveillance as opposed to traditional manual surveillance. In reality, a combined surveillance approach may provide the best possible result. A clear understanding of the epidemiologic principles, such as prevalence and incidence, and some of the nuances behind these principles are essential for the proper interpretation of the epidemiologic data.
    Infectious disease clinics of North America 03/2011; 25(1):261-70. · 2.29 Impact Factor
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    ABSTRACT: The tuberculin skin test (TST) is an important tool for the detection of latent tuberculosis (TB) and the identification of health care workers (HCWs) who require chemoprophylaxis. Although TST is inexpensive, easily available and the preferred test in most TB-prevalent settings, it has recognised limitations, including subjective interpretation, false positivity, cross reactivity with non-tuberculous mycobacteria, administration errors and the requirement for two visits. Given these limitations and the unavailability of better screening tests in resource-limited settings, the acceptance rate for chemoprophylaxis among HCWs has remained low. Furthermore, chemoprophylaxis in these settings is complicated by the high rate of drug-resistant TB, potential adverse reactions, prescription of chemoprophylaxis in undiagnosed active TB patients and the unavailability of follow-up systems provided by occupational health programmes. In the present article, we provide our viewpoint and a practical approach along with existing evidence supporting or discouraging the use of TST and isoniazid chemoprophylaxis for TB screening and management among HCWs in TB-prevalent settings.
    The International Journal of Tuberculosis and Lung Disease 01/2011; 15(1):14-23. · 2.76 Impact Factor
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    ABSTRACT: Endotracheal (ET) tubes accumulate a biofilm during use, which can harbor potentially pathogenic microorganisms. The enrichment of pathogenic strains in the biofilm may lead to ventilator-associated pneumonia (VAP) with an increased morbidity rate in intensive care units. We used quantitative PCR (qPCR) and gene surveys targeting 16S rRNA genes to quantify and identify the bacterial community to detect fastidious/nonculturable organisms present among extubated ET tubes. We collected eight ET tubes with intubation periods between 12 h and 23 d from different patients in a surgical and a medical intensive care unit. Our qPCR data showed that ET tubes were colonized within 24 h. However, the variation between patients was too high to find a positive correlation between the bacterial load and intubation period. We obtained 1263 near full-length 16S rRNA gene sequences from the diverse bacterial communities. Over 70% of these sequences were associated with genera of typical oral flora, while only 6% were associated with gastrointestinal flora. The most common genus identified was Streptococcus (348/1263), followed by Prevotella (179/1263), and Neisseria (143/1263) with the highest relative concentrations for ET tubes with short intubation periods, indicating oral inoculation of the ET tubes. Our study also shows that even though potentially pathogenic bacteria existed in ET tube biofilms within 24 h of intubation, a longer intubation period increases the opportunity for these organisms to proliferate. In the ET tube that was in place for 23 d, 95% of the sequences belonged to Pseudomonas aeruginosa, which is a bacterial pathogen that is known to out compete commensal bacteria in biofilms, especially during periods of antibiotic treatment. Harboring such pathogens in ET biofilms may increase the chance of VAP, and should be aggressively monitored and prevented.
    International journal of medical microbiology: IJMM 11/2010; 300(7):503-11. · 4.54 Impact Factor
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    ABSTRACT: Central line-associated bloodstream infection (BSI) rates, determined by infection preventionists using the Centers for Disease Control and Prevention (CDC) surveillance definitions, are increasingly published to compare the quality of patient care delivered by hospitals. However, such comparisons are valid only if surveillance is performed consistently across institutions. To assess institutional variation in performance of traditional central line-associated BSI surveillance. We performed a retrospective cohort study of 20 intensive care units among 4 medical centers (2004-2007). Unit-specific central line-associated BSI rates were calculated for 12-month periods. Infection preventionists, blinded to study participation, performed routine prospective surveillance using CDC definitions. A computer algorithm reference standard was applied retrospectively using criteria that adapted the same CDC surveillance definitions. Correlation of central line-associated BSI rates as determined by infection preventionist vs the computer algorithm reference standard. Variation in performance was assessed by testing for institution-dependent heterogeneity in a linear regression model. Forty-one unit-periods among 20 intensive care units were analyzed, representing 241,518 patient-days and 165,963 central line-days. The median infection preventionist and computer algorithm central line-associated BSI rates were 3.3 (interquartile range [IQR], 2.0-4.5) and 9.0 (IQR, 6.3-11.3) infections per 1000 central line-days, respectively. Overall correlation between computer algorithm and infection preventionist rates was weak (ρ = 0.34), and when stratified by medical center, point estimates for institution-specific correlations ranged widely: medical center A: 0.83; 95% confidence interval (CI), 0.05 to 0.98; P = .04; medical center B: 0.76; 95% CI, 0.32 to 0.93; P = .003; medical center C: 0.50, 95% CI, -0.11 to 0.83; P = .10; and medical center D: 0.10; 95% CI -0.53 to 0.66; P = .77. Regression modeling demonstrated significant heterogeneity among medical centers in the relationship between computer algorithm and expected infection preventionist rates (P < .001). The medical center that had the lowest rate by traditional surveillance (2.4 infections per 1000 central line-days) had the highest rate by computer algorithm (12.6 infections per 1000 central line-days). Institutional variability of infection preventionist rates relative to a computer algorithm reference standard suggests that there is significant variation in the application of standard central line-associated BSI surveillance definitions across medical centers. Variation in central line-associated BSI surveillance practice may complicate interinstitutional comparisons of publicly reported central line-associated BSI rates.
    JAMA The Journal of the American Medical Association 11/2010; 304(18):2035-41. · 29.98 Impact Factor
  • Keith F Woeltje, Kathleen M McMullen
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    ABSTRACT: The potential to automate at least part of the surveillance process for health care-associated infections was seen as soon as hospitals began to implement computer systems. Progress toward automated surveillance has been ongoing for the last several decades. But as more information becomes available electronically in the healthcare setting, the promise of electronic surveillance for healthcare-associated infections has become closer to reality. Although true fully automated surveillance is not here yet, significant progress is being made at a number of centers for electronic surveillance of central catheter-associated bloodstream infections, ventilator-associated pneumonia, and other healthcare-associated infections. We review the progress that has been made in this area and issues that need to be addressed as surveillance systems are implemented, as well as promising areas for future development.
    Critical care medicine 08/2010; 38(8 Suppl):S399-404. · 6.15 Impact Factor
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    ABSTRACT: Background: In 1998, BJC Healthcare developed a system-wide collaborative approach to Infection Prevention. The Infection Prevention Specialists (IPSs) at the 12 BJC hospitals establish goals and develop interventions to prevent hospital acquired infections (HAIs) and improve patient outcomes. Over the past ten years, the Infection Prevention and Epidemiology Consortium (IPEC) significantly decreased HAI rates at BJC hospitals. Objective: IPEC’s goal is to improve infection rates by implementing systematic interventions to lower endemic HAI rates and employ rapid responses for epidemics and outbreaks. Methods: IPSs use standardized definitions and data collection tools. A common database is used to generate hospital and system-wide HAI reports. IPEC uses a standardized qualitative form at each hospital to assess current practice compared to recommended practice (e.g., CDC guidelines). When practice deviations are identified at a majority of hospitals, IPEC develops interventions which are then implemented by IPS and multidisciplinary teams at each hospital. Interventions are aimed at changing practice and may include policy and procedure changes, product changes and education. For epidemic or outbreak infections, hospitals requests assistance and prepare epidemiological summaries of the problem. A “SWAT” team is assembled and follows a standard outbreak investigation process, including developing a case definition, identifying additional cases, implementing immediate control measures, and formulating and testing hypotheses. The SWAT team consists of local IPSs and MD epidemiologist; a BJC IPS, BJC MD epidemiologist, BJC clinical epidemiologist, and a data abstractor. Additional members are added as necessary. Chi square for trend is utilized for analysis of rates. Results: Under IPEC’s management, infection rates have decreased in all categories that have been tracked. The central line-associated bloodstream infection (CLABSI) rates decreased from 4.95 per 1000 line days in 2000 to 1.57 per 1000 line days in 2008 (OR= 0.32); ventilator associated pneumonia (VAP) from 7.86 per 1000 ventilator days in 1999 to 1.01 per 1000 ventilator days in 2008 (OR=0.13); coronary artery bypass graft (CABG) surgical site infection (SSI) from 4.73 per 100 procedures in 1999 to 1.75 per 100 procedures in 2008 (OR= 0.5).; and spinal fusion and laminectomy SSI rates from 1.51 per 100 procedures in 1999 to 0.91 in 2008 (OR=0.79). Conclusions: Collaboration between IPS at all system hospitals and corporate staff was accompanied by a steady decrease in rates across many types of HAI. The BJC IPEC provides a model for health systems to implement improvements across multiple types of facilities.
    Fifth Decennial International Conference on Health-Care Related Infections 2010; 03/2010
  • Conference Paper: Keith Woeltje
    Keith Woeltje
    Fifth Decennial International Conference on Health-Care Related Infections 2010; 03/2010
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    ABSTRACT: Background: Between-hospital comparisons of CLABSI rates are improved if surveillance definitions are consistently applied across institutions; however, infection preventionists (IPs) apply surveillance definitions with some subjectivity, degrading inter-observer reliability. EAs rely on objective criteria for CLABSI detection. Objective: 1) To assess the level of agreement between EA and IP surveillance on a sample of positive blood culture episodes. 2) To compare both EA and IP against a standardized review (SR). 3) To assess variation of agreement (heterogeneity) from one intensive care unit (ICU) to another, and whether ignoring episodes with only a single common skin commensal (CSC) improves agreement and reduces heterogeneity. Methods: Seven ICUs (4 MICU, 3 SICU) from 4 medical centers participated (2004-2006). A random sample of positive blood culture episodes was evaluated by three methods: (1) IP: IPs prospectively performed routine CLABSI surveillance using pre-2008 National Healthcare Safety Network (NHSN) surveillance definitions (this rule allowed a single CSC to be considered a true CLABSI if appropriate antibiotic therapy was instituted); (2) EA: an electronic algorithm approximating pre-2008 NHSN definitions was applied retrospectively. (3) SR: a single study IP at each medical center retrospectively performed a blinded standardized review using pre-2008 NHSN definitions. Kappa (K) agreement was assessed between methods, and heterogeneity among ICU-strata was assessed using a chi-square statistic for equality of kappa values (SAS 9.1.3). Analyses were repeated after assigning blood culture episodes with only a single CSC as CLABSI-negative for all 3 methods (post-2008 NHSN approximation). Results: 586 positive blood culture episodes were reviewed (Table). Agreement between EA/IP was poor (K = 0.12, 95% confidence interval [CI] 0.07 0.18). Agreements for EA/SR and IP/SR were equivalent and both higher than EA/IP agreement; however, both had significant heterogeneity among ICU strata. Approximating post-2008 NHSN definitions substantially improved EA/SR agreement (K = 0.59, CI 0.52 0.65), but had little effect on IP/SR agreement. Furthermore, using post-2008 NHSN approximation, there no longer was inter-ICU heterogeneity between EA and SR (P = 0.78), while considerable heterogeneity remained for the IP/SR review (P = 0.02). Conclusions: Using a blinded standardized review as the comparator, after ignoring single CSCs, an electronic algorithm had better agreement and less between-ICU heterogeneity than routine IP surveillance. Significant heterogeneity of agreement between human reviews (IP/SR) suggests that IPs inconsistently apply CLABSI surveillance definitions. Objective methods of surveillance such as EA should lead to more valid inter-institution comparisons of CLABSI rates.
    Fifth Decennial International Conference on Health-Care Related Infections 2010; 03/2010
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    ABSTRACT: Background: Urinary tract infections (UTI) are the most common hospital-acquired infections (HAI), causing increased morbidity and hospital costs among patients. Manual surveillance for catheter-associated urinary tract infections (CAUTI) is labor-intensive and often requires a large proportion of infection preventionist’s time. Automated surveillance of patient medical records and microbiology data regarding urinary catheter usage offers a more efficient method of surveillance. Objective: To compare electronic CAUTI surveillance and manual chart abstraction Methods: Patients with a positive urine culture in three inpatient units at Progress West HealthCare Center, a 72-bed community hospital, between August 1, 2008 and July 31, 2009 were evaluated. Patient admission, microbiology, and urinary catheter usage data were collected manually by chart review. Infection prevention personnel used the Centers for Diseases Control National Health Safety Network definitions to determine "true" CAUTI for manually abstracted data. An automated CAUTI surveillance report was generated through the medical record McKesson Horizon Clinicals database (McKesson, San Francisco). For all inpatients, rules were applied to the electronic data to determine the presence of CAUTI. Condition rules included: (1) patient had a urinary catheter; (2) positive culture results > 48 hours after catheter insertion; and (3) colony count ≥ 100,000 colonies. Sensitivity, specificity, and predictive values, were calculated based on the automated results using manual chart abstraction as the reference standard. Results: During the study period, 1,123 positive urine cultures were reported of which 224 cultures were from inpatients. Of the 224 positive urine cultures, 44 inpatients were evaluated and ten (23%) CAUTI were confirmed by manual chart review (3.8 CAUTI per 1,000 urinary catheter days). Results included symptomatic UTI (SUTI) and asymptomatic bacteriuria (ASB). Automated surveillance generated results with a sensitivity of 100% and specificity of 98%. Table 1. Performance of Automated Surveillance for CAUTI Manual Surveillance Automated Report Positive Negative TOTAL Positive 10 5 15 Negative 0 209 209 TOTAL 10 214 224 Conclusions: Automated surveillance accurately reported all true CAUTI from manual chart abstraction, and 98% of truly non-diseased patients were identified as having no CAUTI. A negative predictive value of 100% indicates that automated surveillance accurately identified and excluded positive cultures not associated with CAUTI. Automated CAUTI surveillance with perfect sensitivity can increase the efficiency of Infection Preventionists and reallocate time spent on infection prevention strategies to reduce HAI. Prevention efforts focused on reducing cultures of ASB patients would improve predictions of true SUTI.
    Fifth Decennial International Conference on Health-Care Related Infections 2010; 03/2010

Publication Stats

409 Citations
152.94 Total Impact Points

Institutions

  • 2006–2014
    • Washington University in St. Louis
      • Department of Medicine
      San Luis, Missouri, United States
  • 2002–2011
    • University of Washington Seattle
      • • Division of General Internal Medicine
      • • Division of Allergy and Infectious Diseases
      Seattle, WA, United States
  • 2009
    • Barnes Jewish Hospital
      San Luis, Missouri, United States