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Dive into the research topics where William E. Trick is active.

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Featured researches published by William E. Trick.


The New England Journal of Medicine | 2001

Control of Vancomycin-Resistant Enterococcus in Health Care Facilities in a Region

Belinda E. Ostrowsky; William E. Trick; Annette H. Sohn; Stephen B. Quirk; Stacey C. Holt; Loretta A. Carson; Bertha C. Hill; Matthew J. Arduino; Matthew J. Kuehnert; William R. Jarvis

BACKGROUND In late 1996, vancomycin-resistant enterococci were first detected in the Siouxland region of Iowa, Nebraska, and South Dakota. A task force was created, and in 1997 the assistance of the Centers for Disease Control and Prevention was sought in assessing the prevalence of vancomycin-resistant enterococci in the regions facilities and implementing recommendations for screening, infection control, and education at all 32 health care facilities in the region. METHODS The infection-control intervention was evaluated in October 1998 and October 1999. We performed point-prevalence surveys, conducted a case-control study of gastrointestinal colonization with vancomycin-resistant enterococci, and compared infection-control practices and screening policies for vancomycin-resistant enterococci at the acute care and long-term care facilities in the Siouxland region. RESULTS Perianal-swab samples were obtained from 1954 of 2196 eligible patients (89 percent) in 1998 and 1820 of 2049 eligible patients (89 percent) in 1999. The overall prevalence of vancomycin-resistant enterococci at 30 facilities that participated in all three years of the study decreased from 2.2 percent in 1997 to 1.4 percent in 1998 and to 0.5 percent in 1999 (P<0.001 by chi-square test for trend). The number of facilities that had had at least one patient with vancomycin-resistant enterococci declined from 15 in 1997 to 10 in 1998 to only 5 in 1999. At both acute care and long-term care facilities, the risk factors for colonization with vancomycin-resistant enterococci were prior hospitalization and treatment with antimicrobial agents. Most of the long-term care facilities screened for vancomycin-resistant enterococci (26 of 28 in 1998 [93 percent] and 23 of 25 in 1999 [92 percent]) and had infection-control policies to prevent the transmission of vancomycin-resistant enterococci (22 of 25 [88 percent] in 1999). All four acute care facilities had screening and infection-control policies for vancomycin-resistant enterococci in 1998 and 1999. CONCLUSIONS An active infection-control intervention, which includes the obtaining of surveillance cultures and the isolation of infected patients, can reduce or eliminate the transmission of vancomycin-resistant enterococci in the health care facilities of a region.


Emerging Infectious Diseases | 2003

Influence of Role Models and Hospital Design on Hand Hygiene of Health Care Workers

Mary G. Lankford; Teresa R. Zembower; William E. Trick; Donna M. Hacek; Gary A. Noskin; Lance R. Peterson

We assessed the effect of medical staff role models and the number of health-care worker sinks on hand-hygiene compliance before and after construction of a new hospital designed for increased access to handwashing sinks. We observed health-care worker hand hygiene in four nursing units that provided similar patient care in both the old and new hospitals: medical and surgical intensive care, hematology/oncology, and solid organ transplant units. Of 721 hand-hygiene opportunities, 304 (42%) were observed in the old hospital and 417 (58%) in the new hospital. Hand-hygiene compliance was significantly better in the old hospital (161/304; 53%) compared to the new hospital (97/417; 23.3%) (p<0.001). Health-care workers in a room with a senior (e.g., higher ranking) medical staff person or peer who did not wash hands were significantly less likely to wash their own hands (odds ratio 0.2; confidence interval 0.1 to 0.5); p<0.001). Our results suggest that health-care worker hand-hygiene compliance is influenced significantly by the behavior of other health-care workers. An increased number of hand-washing sinks, as a sole measure, did not increase hand-hygiene compliance.


The Journal of Thoracic and Cardiovascular Surgery | 2000

Modifiable risk factors associated with deep sternal site infection after coronary artery bypass grafting.

William E. Trick; William E. Scheckler; Jerome I. Tokars; Kevin C. Jones; Mel L. Reppen; Ellen M. Smith; William R. Jarvis

OBJECTIVE Our objective was to identify risk factors for deep sternal site infection after coronary artery bypass grafting at a community hospital. METHODS We compared the prevalence of deep sternal site infection among patients having coronary artery bypass grafting during the study (January 1995-March 1998) and pre-study (January 1992-December 1994) periods. We compared any patient having a deep sternal site infection after coronary artery bypass graft surgery during the study period (case-patients) with randomly selected patients who had coronary artery bypass graft surgery but no deep sternal site infection during the same period (control-patients). RESULTS Deep sternal site infections were significantly more common during the study than during the pre-study period (30/1796 [1.7%] vs 9/1232 [0.7%]; P =.04). Among 30 case-patients, 29 (97%) returned to the operating room for sternal debridement or rewiring, and 2 (7%) died. In multivariable analyses, cefuroxime receipt 2 hours or more before incision (odds ratio = 5.0), diabetes mellitus with a preoperative blood glucose level of 200 mg/dL or more (odds ratio = 10.2), and staple use for skin closure (odds ratio = 4.0) were independent risk factors for deep sternal site infection. Staple use was a risk factor only for patients with a normal body mass index. CONCLUSIONS Appropriate timing of antimicrobial prophylaxis, control of preoperative blood glucose levels, and avoidance of staple use in patients with a normal body mass index should prevent deep sternal site infection after coronary artery bypass graft operations.


JAMA | 2010

Quality of traditional surveillance for public reporting of nosocomial bloodstream infection rates.

Michael Y. Lin; Bala Hota; Yosef Khan; Keith F. Woeltje; Tara Borlawsky; Joshua A. Doherty; Kurt B. Stevenson; Robert A. Weinstein; William E. Trick

CONTEXT 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. OBJECTIVE To assess institutional variation in performance of traditional central line-associated BSI surveillance. DESIGN, SETTING, AND PARTICIPANTS 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. MAIN OUTCOME MEASURES 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. RESULTS 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). CONCLUSIONS 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.


Emerging Infectious Diseases | 2004

Computer Algorithms To Detect Bloodstream Infections

William E. Trick; Brandon M. Zagorski; Jerome I. Tokars; Michael O. Vernon; Sharon F. Welbel; Mary F. Wisniewski; Chesley L. Richards; Robert A. Weinstein

Automated bloodstream infection surveillance using electronic data is an accurate alternative to surveillance using manually collected data.


Infection Control and Hospital Epidemiology | 2007

Multicenter intervention program to increase adherence to hand hygiene recommendations and glove use and to reduce the incidence of antimicrobial resistance.

William E. Trick; Michael O. Vernon; Sharon F. Welbel; Patricia L. DeMarais; Mary K. Hayden; Robert A. Weinstein

OBJECTIVE To determine whether a multimodal intervention could improve adherence to hand hygiene and glove use recommendations and decrease the incidence of antimicrobial resistance in different types of healthcare facilities. DESIGN Prospective, observational study performed from October 1, 1999, through December 31, 2002. We monitored adherence to hand hygiene and glove use recommendations and the incidence of antimicrobial-resistant bacteria among isolates from clinical cultures. We evaluated trends in and predictors for adherence and preferential use of alcohol-based hand rubs, using multivariable analyses. SETTING Three intervention hospitals (a 660-bed acute and long-term care hospital, a 120-bed community hospital, and a 600-bed public teaching hospital) and a control hospital (a 700-bed university teaching hospital).Intervention. At the intervention hospitals, we introduced or increased the availability of alcohol-based hand rub, initiated an interactive education program, and developed a poster campaign; at the control hospital, we only increased the availability of alcohol-based hand rub. RESULTS We observed 6,948 hand hygiene opportunities. The frequency of hand hygiene performance or glove use significantly increased during the study period at the intervention hospitals but not at the control hospital; the maximum quarterly frequency of hand hygiene performance or glove use at intervention hospitals (74%, 80%, and 77%) was higher than that at the control hospital (59%). By multivariable analysis, preferential use of alcohol-based hand rubs rather than soap and water for hand hygiene was more likely among workers at intervention hospitals compared with nonintervention hospitals (adjusted odds ratio, 4.6 [95% confidence interval, 3.3-6.4]) and more likely among physicians (adjusted odds ratio, 1.4 [95% confidence interval, 1.2-1.8]) than among nurses at intervention hospitals. A significantly reduced incidence of antimicrobial-resistant bacteria among isolates from clinical culture was found at a single intervention hospital, which had the greatest increase in the frequency of hand hygiene performance. CONCLUSIONS During a 3-year period, a multimodal intervention program increased adherence to hand hygiene recommendations, especially to the use of alcohol-based hand rubs. In one hospital, a concomitant reduction was found in the incidence of antimicrobial-resistant bacteria among isolates from clinical cultures.


Clinical Infectious Diseases | 2003

The Use of Economic Modeling to Determine the Hospital Costs Associated with Nosocomial Infections

Rebecca R. Roberts; R. Douglas Scott; Ralph L. Cordell; Steven L. Solomon; Lynn Steele; Linda M. Kampe; William E. Trick; Robert A. Weinstein

Hospital-associated infection is well recognized as a patient safety concern requiring preventive interventions. However, hospitals are closely monitoring expenditures and need accurate estimates of potential cost savings from such prevention programs. We used a retrospective cohort design and economic modeling to determine the excess cost from the hospital perspective for hospital-associated infection in a random sample of adult medical patients. Study patients were classified as being not infected (n=139), having suspected infection (n=8), or having confirmed infection (n=17). Severity of illness and intensive unit care use were both independently associated with increased cost. After controlling for these confounding effects, we found an excess cost of


Clinical Infectious Diseases | 2013

The Importance of Long-term Acute Care Hospitals in the Regional Epidemiology of Klebsiella pneumoniae Carbapenemase–Producing Enterobacteriaceae

Michael Y. Lin; Rosie Lyles-Banks; Karen Lolans; David W. Hines; Joel B. Spear; Russell Petrak; William E. Trick; Robert A. Weinstein; Mary K. Hayden; Prevention Epicenters Program

6767 for suspected infection and


JAMA | 2012

Effect of Screening for Partner Violence on Women's Quality of Life: A Randomized Controlled Trial

Joanne Klevens; Romina Kee; William E. Trick; Diana Garcia; Francisco Angulo; Robin Jones; Laura S. Sadowski

15,275 for confirmed hospital-acquired infection. The economic model explained 56% of the total variability in cost among patients. Hospitals can use these data when evaluating potential cost savings from effective infection-control measures.


The Journal of Infectious Diseases | 1999

Regional Dissemination of Vancomycin-Resistant Enterococci Resulting from Interfacility Transfer of Colonized Patients

William E. Trick; Matthew J. Kuehnert; Stephen B. Quirk; Matthew J. Arduino; Sonia M. Aguero; Loretta A. Carson; Bertha C. Hill; Shailen N. Banerjee; William R. Jarvis

BACKGROUND In the United States, Klebsiella pneumoniae carbapenemase (KPC)-producing Enterobacteriaceae are increasingly detected in clinical infections; however, the colonization burden of these organisms among short-stay and long-term acute care hospitals is unknown. METHODS Short-stay acute care hospitals with adult intensive care units (ICUs) in the city of Chicago were recruited for 2 cross-sectional single-day point prevalence surveys (survey 1, July 2010-January 2011; survey 2, January-July 2011). In addition, all long-term acute care hospitals (LTACHs) in the Chicago region (Cook County) were recruited for a single-day point prevalence survey during January-May 2011. Swab specimens were collected from rectal, inguinal, or urine sites and tested for Enterobacteriaceae carrying blaKPC. RESULTS We surveyed 24 of 25 eligible short-stay acute care hospitals and 7 of 7 eligible LTACHs. Among LTACHs, 30.4% (119 of 391) of patients were colonized with KPC-producing Enterobacteriaceae, compared to 3.3% (30 of 910) of short-stay hospital ICU patients (prevalence ratio, 9.2; 95% confidence interval, 6.3-13.5). All surveyed LTACHs had patients harboring KPC (prevalence range, 10%-54%), versus 15 of 24 short-stay hospitals (prevalence range, 0%-29%). Several patient-level covariates present at the time of survey-LTACH facility type, mechanical ventilation, and length of stay-were independent risk factors for KPC-producing Enterobacteriaceae colonization. CONCLUSIONS We identified high colonization prevalence of KPC-producing Enterobacteriaceae among patients in LTACHs. Patients with chronic medical care needs in long-term care facilities may play an important role in the spread of these extremely drug-resistant pathogens.

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Robert A. Weinstein

Rush University Medical Center

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Michael Y. Lin

Rush University Medical Center

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Bala Hota

Rush University Medical Center

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Mary K. Hayden

Rush University Medical Center

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William R. Jarvis

Centers for Disease Control and Prevention

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Keith F. Woeltje

Washington University in St. Louis

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Lance R. Peterson

NorthShore University HealthSystem

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Michael O. Vernon

NorthShore University HealthSystem

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