Keith F Woeltje

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

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Publications (49)178.51 Total impact

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    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. DOI:10.1086/678602 · 3.94 Impact Factor
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    ABSTRACT: Mechanical ventilation provides an important, life-saving therapy for severely ill patients, but ventilated patients are at an increased risk for complications, poor outcomes, and death during hospitalization. 1 The timely measurement of negative outcomes is important in order to identify potential issues and to minimize the risk to patients. The Centers for Disease Control and Prevention (CDC) created an algorithm for identifying Ventilator-Associated Events (VAE) in adult patients for reporting to the National Healthcare Safety Network (NHSN). Currently, the primarily manual surveillance tools require a significant amount of time from hospital infection prevention (IP) staff to apply and interpret. This paper describes the implementation of an electronic VAE tool using an internal clinical data repository and an internally developed electronic surveillance system that resulted in a reduction of labor efforts involved in identifying VAE at Barnes Jewish Hospital (BJH).
    AMIA; 11/2014
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    ABSTRACT: Mechanical ventilation provides an important, life-saving therapy for severely ill patients, but ventilated patients are at an increased risk for complications, poor outcomes, and death during hospitalization.1 Using electronic health record (EHR) systems along with microbiology, vital signs, and antibiotic data, BJC HealthCare implemented an electronic Ventilator-Associated Event (VAE) tool and incorporated it within an existing, intranet based, electronic surveillance system. 2 Incorporating the electronic VAE tool resulted in a reduction of Infection Prevention (IP) labor efforts involved in identifying VAE cases and provided a foundation for electronic reporting of VAE cases to the National Healthcare Safety Network (NHSN).
    AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium 11/2014;
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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. DOI:10.1086/677623 · 3.94 Impact Factor
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    ABSTRACT: Hospitalized patients on mechanical ventilation are at high risk for complications and poor outcomes, including death. Using electronic health (EHR) record systems and adopting the Ventilator-Associated Events (VAE) algorithm proposed by the CDC NHSN, we are developing an algorithm for electronic surveillance of VAE occurring in mechanically ventilated adult patients. Results from this algorithm will be used to trend VAE, and intervene in areas with higher than expected rates.
    AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium 11/2013;
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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; 133(1). DOI:10.1016/j.thromres.2013.09.011 · 2.43 Impact Factor
  • Keith F Woeltje, Hilary M Babcock
    Canadian Medical Association Journal 08/2013; 185(11):983-4. DOI:10.1503/cmaj.113-2124 · 5.81 Impact Factor
  • American Journal of Infection Control 06/2013; 41(6):S23-S24. DOI:10.1016/j.ajic.2013.03.048 · 2.33 Impact Factor
  • American Journal of Infection Control 06/2013; 41(6):S51. DOI:10.1016/j.ajic.2013.03.108 · 2.33 Impact Factor
  • Infection Control and Hospital Epidemiology 06/2013; 34(6):655-6. DOI:10.1086/670643 · 3.94 Impact Factor
  • K F Woeltje
    The Journal of hospital infection 05/2013; 84(2). DOI:10.1016/j.jhin.2013.03.005 · 2.78 Impact Factor
  • Infection Control and Hospital Epidemiology 09/2012; 33(9):952-4. DOI:10.1086/667394 · 3.94 Impact Factor
  • American Journal of Infection Control 06/2012; 40(5):e134-e135. DOI:10.1016/j.ajic.2012.04.237 · 2.33 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
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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. DOI:10.1086/662181 · 3.94 Impact Factor
  • American Journal of Infection Control 06/2011; 39(5):E30–E31. DOI:10.1016/j.ajic.2011.04.077 · 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. DOI:10.1016/j.idc.2010.11.013 · 2.31 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: 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. DOI:10.1001/jama.2010.1637 · 30.39 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. DOI:10.1016/j.ijmm.2010.02.005 · 3.42 Impact Factor