J. Skufca, J. Ollgren, M. Virtanen, K. Huotari, O. Lyytikäinen
{"title":"Interhospital Comparison of Surgical Site Infection Rates in Orthopedic Surgery","authors":"J. Skufca, J. Ollgren, M. Virtanen, K. Huotari, O. Lyytikäinen","doi":"10.1017/ice.2016.333","DOIUrl":"https://doi.org/10.1017/ice.2016.333","url":null,"abstract":"OBJECTIVE To investigate whether comparison by deep or adjusted deep surgical site infection (SSI) rates in orthopedic surgeries are a better basis for feedback to Finnish hospitals than overall SSI rates DESIGN Retrospective cohort study SETTING Hospitals conducting surveillance of hip arthroplasties (HPROs) and knee arthroplasties (KPROs) in the Finnish Hospital Infection Program METHODS We analyzed surveillance data for 73,227 HPROs and 56,860 KPROs performed in 18 hospitals during 1999–2014. For each hospital, the overall, deep, and adjusted deep SSI rates with 95% confidence intervals (CIs) were calculated, and the hospital ranks were simulated in the Bayesian framework. Adjustments were performed using relevant patient and hospital characteristics. The correlation between the median expected hospital ranks in overall versus deep SSI rates and deep vs adjusted deep SSI rates were assessed using Spearman’s correlation coefficient ρ. RESULTS For HPRO, the overall SSI rates ranged from 0.92 to 6.83, the deep SSI rates ranged from 0.34 to 1.86, and the adjusted deep hospital-specific SSI rates ranged from 0.37 to 1.85. For KPRO, the overall SSI rates ranged from 0.71 to 5.03, the deep SSI rates ranged from 0.42 to 1.60, and the adjusted deep hospital-specific SSI rates ranged from 0.56 to 1.55. For both procedures, the 95% CIs of the rates between hospitals largely overlapped; only single outliers were detected. Hospital rank did not correlate between overall and deep SSI rates (HPRO, ρ=0.03; KPRO, ρ=0.40), but a correlation was observed in hospital rank for deep and adjusted deep SSI rates (HPRO, ρ=0.85; KPRO, ρ=0.94). CONCLUSION Deep SSI rates may be a better tool for interhospital comparisons than overall SSI rates. Although the adjustment could lead to fairer hospital ranking, it is not always necessary for feedback. Infect Control Hosp Epidemiol 2017;38:423–429","PeriodicalId":13655,"journal":{"name":"Infection Control & Hospital Epidemiology","volume":"99 1","pages":"423 - 429"},"PeriodicalIF":0.0,"publicationDate":"2017-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79297794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Kuhle, J. Carter, S. Kirkland, J. Langley, B. Maguire, Bruce Smith
{"title":"Reply to Weber, von Cube, Sommer, Wolkewitz: Necessity of a Competing Risk Approach in Risk Factor Analysis of Central-Line–Associated Bloodstream Infection","authors":"S. Kuhle, J. Carter, S. Kirkland, J. Langley, B. Maguire, Bruce Smith","doi":"10.1017/ice.2016.331","DOIUrl":"https://doi.org/10.1017/ice.2016.331","url":null,"abstract":"To the Editor—We thank Ms. Weber and colleagues for their comments regarding the use of the Cox proportional hazards model to analyze risk factors for central-line–associated bloodstream infections (CLABSIs) in children, in which we used a Cox proportional hazards model to determine risk factors for this outcome. In our analysis, removal of the central venous cathether was treated as censoring. Weber et al suggest that removal of the line constitutes a competing risk for CLABSI because children without a line can no longer be assumed to be at the same risk for CLABSI than those with a line (the fundamental assumption of censoring). We sincerely appreciate these comments, which highlight the need for increased awareness of the assumptions of the Cox proportional hazard method in this setting. We agree that removal of the central venous catheter indeed constitutes a competing risk. In our cohort study, there were only 2 possible outcomes with regard to the life of the central venous catheter: infection and catheter removal. Because all lines are followed by the infection control team until removal, there was no censoring due to loss to follow-up. We have re-analyzed the data and have graphed the cumulative incidence function of CLABSI as suggested by Weber et al. The curve reaches the empirical cumulative incidence of CLABSI of 6.8% on the day of the last event (Figure 1). We have further rerun the Cox proportional hazards model using (1) the subdistribution hazard (SHR) approach and (2) the cause-specific hazard approach (modeling the time to line infection or catheter removal separately, each time treating the other as the censoring event). After reviewing the literature and in discussion with statistician colleagues, we feel that the first approach (SHR) is not suitable to answer our research question. The SHR approach describes the CLABSI risk in patients who already had their line removed (the competing event), ie, in a non-existing, theoretical population. This approach has been advocated in the literature for prediction modeling rather than etiologic research (like our study). By contrast, the hazard ratios from the cause-specific models can be interpreted as the risk of CLABSI in patients who have not (yet) had CLABSI and have not had their catheter removed (the competing event). Within this interpretation of the hazard ratios, the estimates presented in our paper are correct.","PeriodicalId":13655,"journal":{"name":"Infection Control & Hospital Epidemiology","volume":"4 1","pages":"511 - 511"},"PeriodicalIF":0.0,"publicationDate":"2017-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79905040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Sloane, C. Kistler, D. Reed, D. Weber, Kimberly T Ward, S. Zimmerman
{"title":"Urine Culture Testing in Community Nursing Homes: Gateway to Antibiotic Overprescribing","authors":"P. Sloane, C. Kistler, D. Reed, D. Weber, Kimberly T Ward, S. Zimmerman","doi":"10.1017/ice.2016.326","DOIUrl":"https://doi.org/10.1017/ice.2016.326","url":null,"abstract":"OBJECTIVE To describe current practice around urine testing and identify factors leading to overtreatment of asymptomatic bacteriuria in community nursing homes (NHs) DESIGN Observational study of a stratified random sample of NH patients who had urine cultures ordered in NHs within a 1-month study period SETTING 31 NHs in North Carolina PARTICIPANTS 254 NH residents who had a urine culture ordered within the 1-month study period METHODS We conducted an NH record audit of clinical and laboratory information during the 2 days before and 7 days after a urine culture was ordered. We compared these results with the urine antibiogram from the 31 NHs. RESULTS Empirical treatment was started in 30% of cases. When cultures were reported, previously untreated cases received antibiotics 89% of the time for colony counts of ≥100,000 CFU/mL and in 35% of cases with colony counts of 10,000–99,000 CFU/mL. Due to the high rate of prescribing when culture results returned, 74% of these patients ultimately received a full course of antibiotics. Treated and untreated patients did not significantly differ in temperature, frequency of urinary signs and symptoms, or presence of Loeb criteria for antibiotic initiation. Factors most commonly associated with urine culture ordering were acute mental status changes (32%); change in the urine color, odor, or sediment (17%); and dysuria (15%). CONCLUSIONS Urine cultures play a significant role in antibiotic overprescribing. Antibiotic stewardship efforts in NHs should include reduction in culture ordering for factors not associated with infection-related morbidity as well as more scrutiny of patient condition when results become available. Infect Control Hosp Epidemiol 2017;38:524–531","PeriodicalId":13655,"journal":{"name":"Infection Control & Hospital Epidemiology","volume":"24 1","pages":"524 - 531"},"PeriodicalIF":0.0,"publicationDate":"2017-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86567534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Challenging Residual Contamination of Instruments for Robotic Surgery in Japan","authors":"N. von Landenberg, A. Cole, P. Gild, Q. Trinh","doi":"10.1017/ice.2016.334","DOIUrl":"https://doi.org/10.1017/ice.2016.334","url":null,"abstract":"Affiliations: 1. Indiana University School of Medicine, Indianapolis, Indiana; 2. Indiana State Department of Health, Indianapolis, Indiana. Address correspondence to Andrew T. Dysangco, MD, 545 Barnhill Dr. Emerson Hall, Suite 421, Indianapolis, IN 46202-5124 (andysang@iupui. edu). PREVIOUS PRESENTATION: These findings were presented as a poster in the SHEA Spring Conference, May 19, 2016, in Atlanta, Georgia.","PeriodicalId":13655,"journal":{"name":"Infection Control & Hospital Epidemiology","volume":" 2","pages":"501 - 502"},"PeriodicalIF":0.0,"publicationDate":"2017-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91411803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Measures to Prevent and Control Vancomycin-Resistant Enterococci: Do They Really Matter?","authors":"H. Humphreys","doi":"10.1017/ice.2016.329","DOIUrl":"https://doi.org/10.1017/ice.2016.329","url":null,"abstract":"present. Contaminated urine cultures (≥3 organisms present) were misclassified as infections in 6 of 58 cases (10.3%), and in 5 of 58 cases (8.6%), no urine culture was obtained. Lastly, in 15 of 58 cases (25.9%), bacteriuria was present (1 or 2 organisms), but the colony count did not reach the NHSN metric threshold of ≥ 100,000 CFU/mL. The study period comprised 233,921 patient days. The CAUTI rate was 0.24 CAUTIs per 1,000 patient days using the ICD-10-CM metric; this rate was 0.18 when POA cases were eliminated. The CAUTI rate was 0.20 per 1,000 patient days using the NHSN metric. The NHSN CAUTI metric and the ICD-10-CM CAUTI-like code produce widely discrepant results. Even when ICD-10 cases that were POA were removed to better align with the NHSN criteria, the sensitivity of the ICD-10 metric was only 2.4%. Importantly, no patient safety indicator from AHRQ is available for CAUTI as there is for central venous catheterrelated bloodstream infection. This was the primary reason that we used the administrative code (ICD-10-CM) to compare to NHSN surveillance data for detecting CAUTI. Our results demonstrate that updating ICD-9-CMwith more codes to produce ICD-10-CM did not improve the ability of administrative data to identify CAUTIs. The date of the event is an important element used to meet an NHSN site-specific infection criterion, including CAUTI, and that is one reason that administrative data fail to accurately identify cases of HAI. This study has several limitations. First, it was performed in a single medical center. In addition, we did not review the negative cases via either method, and we assumed that traditional surveillance (NHSN) is the gold standard surveillance method. Therefore, it was not possible to calculate the specificity because our aim was to compare only NHSN and ICD-10-CM CAUTI identified cases. Given that CAUTI is a relatively rare event, we can assume that the specificity of the ICD-10-CM metric is high. In summary, we found that ICD-10-CM has an extremely low sensitivity for detecting CAUTI cases; it failed to detect 98.3% of the infections at our institution. Almost all cases identified via ICD-10-CM did not fulfill the NHSN criteria. Thus, administrative coding for this HAI is not a useful tool for use as a surveillance method.","PeriodicalId":13655,"journal":{"name":"Infection Control & Hospital Epidemiology","volume":"12 1","pages":"507 - 509"},"PeriodicalIF":0.0,"publicationDate":"2017-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80753664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Kelly, Makoto M. Jones, K. Echevarria, S. Kralovic, M. Samore, M. Goetz, K. Madaras-Kelly, L. Simbartl, A. Morreale, M. Neuhauser, G. Roselle
{"title":"A Report of the Efforts of the Veterans Health Administration National Antimicrobial Stewardship Initiative","authors":"A. Kelly, Makoto M. Jones, K. Echevarria, S. Kralovic, M. Samore, M. Goetz, K. Madaras-Kelly, L. Simbartl, A. Morreale, M. Neuhauser, G. Roselle","doi":"10.1017/ice.2016.328","DOIUrl":"https://doi.org/10.1017/ice.2016.328","url":null,"abstract":"OBJECTIVE To detail the activities of the Veterans Health Administration (VHA) Antimicrobial Stewardship Initiative and evaluate outcomes of the program. DESIGN Observational analysis. SETTING The VHA is a large integrated healthcare system serving approximately 6 million individuals annually at more than 140 medical facilities. METHODS Utilization of nationally developed resources, proportional distribution of antibiotics, changes in stewardship practices and patient safety measures were reported. In addition, inpatient antimicrobial use was evaluated before and after implementation of national stewardship activities. RESULTS Nationally developed stewardship resources were well utilized, and many stewardship practices significantly increased, including development of written stewardship policies at 92% of facilities by 2015 (P<.05). While the proportional distribution of antibiotics did not change, inpatient antibiotic use significantly decreased after VHA Antimicrobial Stewardship Initiative activities began (P<.0001). A 12% decrease in antibiotic use was noted overall. The VHA has also noted significantly declining use of antimicrobials prescribed for resistant Gram-negative organisms, including carbapenems, as well as declining hospital readmission and mortality rates. Concurrently, the VHA reported decreasing rates of Clostridium difficile infection. CONCLUSIONS The VHA National Antimicrobial Stewardship Initiative includes continuing education, disease-specific guidelines, and development of example policies in addition to other highly utilized resources. While no specific ideal level of antimicrobial utilization has been established, the VHA has shown that improving antimicrobial usage in a large healthcare system may be achieved through national guidance and resources with local implementation of antimicrobial stewardship programs. Infect Control Hosp Epidemiol 2017;38:513–520","PeriodicalId":13655,"journal":{"name":"Infection Control & Hospital Epidemiology","volume":"55 1","pages":"513 - 520"},"PeriodicalIF":0.0,"publicationDate":"2017-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84495550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yin-Yin Chen, Wan-Tsuei Huang, Chia-Ping Chen, Shu-mei Sun, Fu-Mei Kuo, Y. Chan, S. Kuo, Fu-Der Wang
{"title":"An Outbreak of Ralstonia pickettii Bloodstream Infection Associated with an Intrinsically Contaminated Normal Saline Solution","authors":"Yin-Yin Chen, Wan-Tsuei Huang, Chia-Ping Chen, Shu-mei Sun, Fu-Mei Kuo, Y. Chan, S. Kuo, Fu-Der Wang","doi":"10.1017/ice.2016.327","DOIUrl":"https://doi.org/10.1017/ice.2016.327","url":null,"abstract":"OBJECTIVE Ralstonia pickettii has caused contamination of pharmaceutical solutions in many countries, resulting in healthcare infections or outbreak events. We determined the source of the outbreak of R. pickettii bloodstream infection (BSI). METHODS This study was conducted in a 3,000-bed tertiary referral medical center in Taiwan with >8,500 admissions during May 2015. Patients had been treated in the injection room or chemotherapy room at outpatient departments, emergency department, or hospital wards. All patients who were culture positive for R. pickettii from May 3 to June 11, 2015, were eligible for the study. The aim of the survey was to conduct clinical epidemiological and microbiological investigations to identify possible sources of infection. RESULTS We collected 57 R. pickettii–positive specimens from 30 case patients. We performed 24 blood cultures; 14 of these revealed >2 specimens and 6 used fluid withdrawn from Port-a-Cath implantable venous access devices. All patients received an injection of 20 mL 0.9% normal saline via catheter flushing. In addition, 2 unopened ampules of normal saline solution (20 mL) were confirmed positive for R. pickettii. The Taiwan Centers for Disease Control and Prevention performed sampling and testing of the same manufactured batch and identified the same strain of R. pickettii. Pulsed-field gel electrophoresis tests revealed that all clinical isolates had similarity of >90%, validating the outbreak of the same clone of R. pickettii. CONCLUSIONS R. pickettii can grow in saline solutions and cause bloodstream infections. Hospital monitoring mechanisms are extremely important measures in identifying and ending such outbreaks. Infect Control Hosp Epidemiol 2017;38:444–448","PeriodicalId":13655,"journal":{"name":"Infection Control & Hospital Epidemiology","volume":"86 1","pages":"444 - 448"},"PeriodicalIF":0.0,"publicationDate":"2017-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83770578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}