- Email: [email protected]
Ten-year surveillance of central line–associated bloodstream infections in South Korea: Surveillance not enough, action needed
ARTICLE IN PRESS American Journal of Infection Control 000 (2019) 1−5
Contents lists available at ScienceDirect
American Journal of Infection Control journal homepage: www.ajicjournal.org
Major Article
Ten-year surveillance of central line−associated bloodstream infections in South Korea: Surveillance not enough, action needed Eun Jin Kim MD a, So Young Kang PhD b, Yee Gyung Kwak MD, PhD c, Sung Ran Kim RN d, Myoung Jin Shin RN e, Hyeon Mi Yoo RN f, Su Ha Han RN g, Dong Wook Kim PhD h, Young Hwa Choi MD, PhD a,*, the Steering Committee of KONIS a
Department of Infectious Diseases, Ajou University School of Medicine, Suwon, South Korea Office of Biostatistics, Institute of Medical Sciences, Ajou University School of Medicine, Suwon, South Korea c Department of Internal Medicine, Inje University Ilsan Paik Hospital, Goyang, South Korea d Infection Control Office, Korea University Guro Hospital, Seoul, South Korea e Infection Control Office, Seoul National University Bundang Hospital, Seongnam, South Korea f Infection Control Office, Inje University Sanggye Paik Hospital, Seoul, South Korea g Department of Nursing, Soonchunhyang University College of Medicine, Cheonan, South Korea h Department of Policy Research Affairs, National Health Insurance Service Ilsan Hospital, Goyang, South Korea b
Key Words: Intensive care units Healthcare-associated infections Blood stream infections Korean National Healthcare-associated Infections Surveillance System (KONIS)
Background: Central line−associated bloodstream infections (CLABSIs) are preventable health care−associated infections that can lead to increased mortality. Therefore, we investigated trends in CLABSI rates, and the factors associated with changing trends over a 10-year period using the Korean National Healthcareassociated Infections Surveillance System (KONIS). Methods: We investigated annual CLABSI rates from 2006 to 2015 in 190 KONIS-participating intensive care units (ICUs) from 107 participating hospitals. We collected data associated with hospital and ICU characteristics and analyzed trends using generalized autoregressive moving average models. Results: The CLABSI pooled mean rate decreased from 3.40 in 2006 to 2.20 in 2015 (per 1,000 catheter-days). The trend analysis also showed a significant decreasing trend in CLABSI rates in unadjusted models (annual increase, −0.137; P < .001). After adjusting for hospital and ICU characteristics, significant decreasing trends were identified (annual increase, −0.109; P < .001). However, there were no significant changes in subgroups with non-university-affiliated hospitals, hospitals in metropolitan areas near Seoul, small hospitals (300-699 beds), or surgical ICUs. Conclusions: In South Korea, CLABSI rates have shown significant reductions in the past 10 years with participation in the KONIS. However, CLABSI rates may be reduced by encouraging more hospitals to participate in the KONIS and by improved policy support for hospitals lacking infection control resources. © 2019 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
A central line−associated bloodstream infection (CLABSI) is a laboratory-confirmed bloodstream infection (BSI) in a patient who has had a central line within the 48 hours prior to BSI development, which is unrelated to an infection at another site.1,2 Although these infections are preventable, it is well-known that CLABSI increases * Address correspondence to Young Hwa Choi, MD, PhD, Department of Infectious Diseases, Ajou University School of Medicine, 164, World cup-ro, Yeongtong-gu, 16499 Suwon-si, Gyeonggi-do, South Korea. E-mail address: [email protected] (Y.H. Choi). Funding/support: This work was supported by the Research Program [2016E2300200] funded by the Korea Center for Disease Control and Prevention, 2016. Conflicts of interest: None to report.
mortality and morbidity, and also leads to increased medical costs.3 Therefore, in South Korea, we have continuously monitored health care−associated infections (HAIs), including CLABSI, in intensive care units (ICUs) through the Korean National Healthcare-associated Infections Surveillance System (KONIS) program, run by the Korea Center for Disease Control and Prevention and the Korean Society for Healthcare-associated Infection Control and Prevention. The experience of the National Healthcare Safety Network (NHSN) in the United States was taken into consideration when developing the KONIS, and this system focuses on the surveillance and prevention of device-associated infections (DAIs) in adult patients in ICUs.4,5
https://doi.org/10.1016/j.ajic.2019.07.020 0196-6553/© 2019 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
ARTICLE IN PRESS 2
E.J. Kim et al. / American Journal of Infection Control 00 (2019) 1−5
A trend analysis was performed based on 10 years of observations from the KONIS, which was established in 2006. In particular, we aimed to investigate if this continuous surveillance system helped to reduce the trend in the incidence of HAIs, similar to a study on the efficacy of the nosocomial infection control (SENIC) project, and we examined the effect of surveillance by analyzing trends in incidence according to the characteristics of each hospital and ICU.6 We also evaluated year-wise time trends of CLABSI rates in ICUs that continuously participated in the KONIS from 2007-2015. METHODS KONIS system The KONIS involved prospective surveillance of HAI, including CLABSI rates and central line-device use ratios, in participating ICUs between 2006 and 2015. The definitions of CLABSI and central linedevice utilization ratios were standardized and based on those of the Centers for Disease Control of Prevention/NHSN system.7 Investigators were provided with a manual and training tool containing a detailed description of how surveillance must be performed, and complete surveillance forms to ensure standardized implementation. In addition, we conducted regular training twice yearly, and all data were validated externally.8 Surveillance Trained infection preventionists (IPs) collected data from ICU patients in participating hospitals. All patients who stayed in the ICU for >2 days were included in the surveillance and were followed up from admission until discharge or death. After ICU discharge, patients were followed up for infection for an additional 2 days. Device-associated HAI rates were calculated as the number of infections per 1,000 device-days, and device use was calculated as a ratio of total devicedays to total patient-days. The pooled incidences of DAIs and device utilization ratios were calculated for each year of participation. We also collected data on the organizational and institutional characteristics of the included hospitals and ICUs, such as hospital location; total number of beds in the hospital and ICU; type of ICU; the number of ICU nursing staff, IPs, and infectious disease professionals; and whether the hospital was a major teaching hospital, a private hospital, or a university-affiliated hospital. A major teaching hospital was defined as a hospital with programs for medical students and postgraduate medical training (ie, residency and/or fellowships). Hospitals were stratified by the number of beds: 300-699, 700-899, and ≥900. The types of ICUs in this study were as follows: medical ICU (MICU), medical combined ICU (MCICU), surgical combined ICU (SCICU), surgical ICU (SICU), and neurosurgical ICU (NSICU). The ICUs were classified according to the type of patients involved in their care, according to the average department of ICU. An MICU was defined as having >80% of internal medicine patients alone. An SICU and NSICU were defined as having >80% of general surgery and neurosurgery patients, respectively. Other cases were categorized as combined ICU, MCICU, and SCICU. Consecutive participating hospitals Although the survey was initiated in September 2006, the duration in 2006 was only half a year. Since 2007, there has been greater participation, and the organization of the conference of the Korean Society for Healthcare-associated Infection Control and Prevention and KONIS Board has improved. From 2007, we analyzed only hospitals that participated every year until 2015. These hospitals will be able to accurately represent the benefits of KONIS’ continued involvement.
Statistical analyses Analysis of trends was performed using the generalized autoregressive moving average (GARMA) to account for serial correlation.9 Trends that were adjusted for organizational and institutional characteristics of the hospitals and ICUs (such as hospital location, total number of beds in the hospital and ICU, type of ICU, the number of IPs and infectious disease professionals, and whether the hospital was a university-affiliated hospital), and unadjusted trends in CLABSI rates were estimated using a GARMA model. Epi Info version 7 (Centers for Disease Control of Prevention, Atlanta, GA) and SAS statistical program version 9.4 (SAS Institute Inc, Cary, NC) were used to conduct data analyses. Statistical significance was considered as P <.05. Ethical declaration This is a study using information disclosed to the general public as national data, and institutional review board approval was exempted from studies that do not collect or record personally identifiable information. RESULTS During the decade of surveillance, linear mixed regression models indicated that CLABSI rates significantly decreased from 3.40 in 2006 to 2.20 in 2015 (per 1,000 catheter-days, F = 14.17; P < .001) (Fig 1A). The trend analysis using GARMA also showed a significant decrease in the rate of CLABSI. In the unadjusted models, a significant downward trend in the rate of CLABSI was observed overall (from 2.99 per 1,000 catheter-days in 2006 to 2.09 per 1,000 catheter-days in 2015; annual increase, −0.137; P < .001). Depending on the type of hospital and ICU, subgroup analysis revealed an almost significant decreasing trend. However, there were no significant changes noted for subgroups of hospitals that were non-university-affiliated, or that were located in metropolitan areas near and around Seoul. In addition, the trend was not significant among the subgroup including small hospitals with 300-699 beds. When classified by ICU characteristics, there was no significant decreasing trend in SICU series as follows SCICU, SICU, and NSICU; however, there was a significant decrease in MICUs. In Supplementary Table S1, the number of participating ICUs that changed annually during the study period is shown. After adjustment for location, hospital size, university-affiliated hospitals, type of ICU, and number of infection specialists, significant decreases in trends of the rate of CLABSI were identified in all participating hospitals (annual increase, −0.109; P < .001) (Fig 1B). After subgroup analysis, the results were similar to those before adjustment. There were no significant changes in trends for subgroups with non-university-affiliated hospitals, hospitals in metropolitan areas near and around Seoul, small hospitals with between 300 and 699 beds, and SICUs (Table 1). Since 2006, analysis of the trend in CLABSI incidence in consecutive participating hospitals, which was consistently recorded from 2007-2015, showed a significant decline in both unadjusted (annual increase, −0.119; P < .001) and adjusted models (annual increase, −0.119; P < .001). Likewise, in subgroup analysis, there was no significant decreasing trend in non-university-affiliated hospitals, metropolitan hospitals in the suburbs of Seoul, small hospitals with 300699 beds, and SICUs (Supplementary Table S2). DISCUSSION In the past decade, CLABSI rates have shown significant reductions using trend analysis in South Korea. Depending on the type of hospital and ICU, subgroup analysis also revealed an almost significant decreasing trend. Therefore, the national surveillance program of
ARTICLE IN PRESS E.J. Kim et al. / American Journal of Infection Control 00 (2019) 1−5
3
Fig 1. Trends in central line−associated bloodstream infection (CLABSI) rates in intensive care units between 2006 and 2015. (A) A scatter plot is presented with the horizontal line representing the trend. The device-associated infection rates (per 1,000 device-days) on the y-axis were calculated as the total number of infections per 1,000 device-days and were multiplied by 1,000 (F = 14.17; P < .001). (B) Model-adjusted CLABSI rate estimates.
10 years was effective in South Korea. As already demonstrated in the SENIC study, national surveillance has a positive impact on the prevention of HAI.6 Several studies have also identified positive effects on the reduction in CLABSI rate by applying a national surveillance program.10,11 Under the leadership of the government, South Korea implemented the national surveillance system in cooperation with the Korean Society of Infectious Disease in 2006. From July 2006, there were 76 participating ICUs from 44 hospitals nationwide that started monitoring HAI. In 2006, we implemented standards and recruited participating hospitals; the unified criteria and methods required for the monitoring of HAIs in ICUs were summarized in the 2006 KONIS manual and were revised biannually.12 In 2007, the number of hospitals participating in the KONIS increased and a new surgical site infection module was added. To improve the accuracy of the KONIS data, a “validation” method was developed and applied in 2008. External validation and guidance manual revision and education were performed every 2 years.8,13 Hospitals with >400 beds were invited to participate at the beginning of 2006, with 44 (33.8%) of 130 hospitals participating nationwide. Since 2010, hospitals with >300 beds have been able to participate, and 72 hospitals (72 of 161, 44.7%) participated in 2010. In 2015, 95 hospitals participated, and the participation rate is increasing every year. It was 55.2% (95 of 172) of all hospitals that can participate in South Korea, which can ensure the generality of this data. In addition, standardization and regular education regarding ICU infection monitoring was consistently performed. Comparison between participating hospitals was made possible, which led to improvements in infection control quality, and as a result, DAI decreased. Of DAIs, CLABSI is an independent risk factor for increased medical costs and prolonged hospitalization period. According to the KONIS data, CLABSI accounts for >85% of total BSIs every year in the ICUs. The mortality rate of CLABSI is known to be approximately 3%, with severe infection approximately 25%. Moreover, it is estimated that the average cost of medical care for CLABSI is an additional $19,633$28,508 per patient.14 Intravascular catheters are used for various purposes, including dialysis, nutrition, drug administration, and intravascular procedures, and use is increasing in the ICU.14-16 Therefore, the reduction in CLABSI after an infection control program is an important issue, and significant effort is required.
As the KONIS used a unified definition of CLABSI and surveillance methods, it was possible to compare infection rates according to the size and area of each hospital. However, interventions, such as using a bundle approach or suggesting guidelines for CLABSI prevention, were not provided. Instead, through constant participation in the KONIS, there was regular lecture-based training on topics such as basic HAI concepts to surveillance methods. Continuous participation has enabled comparison with other hospitals to motivate hospitals to manage their infection rate. This is likely to have contributed to the success of DAI reduction including CLABSI. Furthermore, as shown in Supplementary Table S2, subgroup analysis of hospitals that participated in the KONIS every year since 2007 showed a significant decrease in CLABSI rate. This shows that the KONIS had a positive impact on the infection rate through continuous surveillance. In other respects, subgroup analysis did not show a declining trend for hospitals in areas outside of Seoul, small hospitals, or surgical or non-university hospitals. This suggests that infection control resources are mainly concentrated in hospitals in Seoul, MICUs, and university hospitals. In a previous study, larger hospitals and university-affiliated hospitals were found to have better employment status of infection specialists and hand hygiene resources.17 In the end, it was estimated that the infection rate in smaller hospitals was more likely to reflect the lack of infection control personnel and infection control resources. Thus, with further research, it would be beneficial to investigate whether indicators of improvement change with more intensive support and management in small hospitals. In particular, efforts will need to be made to employ an infectious disease specialist in addition to other efforts to reduce CLABSI after surgery in hospitals beyond the region of Seoul. Numerous studies have reported the effect of surveillance programs in other countries. In Taiwan, the incidence density of HAI decreased by 46.2% from 9.3 episodes to 5.0 episodes per 1,000 patients-day after implementing a national surveillance system from 2006-2015.18 In several studies conducted in both developing and developed countries, participation in national surveillance has been shown to reduce CLABSI by 25%-33%.11,19,20 Compared with other countries, the CLABSI rate is considered to be higher in South Korea than in high-income countries such as the United States, Australia, and Canada, whereas the rate is similar in Northeast Asia (eg, Japan and Taiwan). Additional action is now required to further reduce the
4
Table 1 Central line−associated bloodstream infection rates* in intensive care units during 2006-2015, calculated with the use of 1-year moving averagesy Year 2006 (95% CI)
Subgroup
All participants University-affiliated hospitals Yes No
Southern-metropolitan area{ Size of hospitals 300-699 beds 700-899 beds ≥900 beds Type of ICU MCICU MICU NSICU SCICU SICU Beds per an infection specialist <300 beds ≥300 beds
2009 (95% CI)
2010 (95% CI)
2011 (95% CI)
2012 (95% CI)
2013 (95% CI)
2014 (95% CI)
2015 (95% CI)
Annual increase, 95% CI
P value
Annual increase, 95% CI
P valuex
2.99 (2.46-3.52)
2.8 (2.36-3.24)
3.29 (2.86-3.72)
2.93 (2.56-3.3)
2.74 (2.36-3.12)
2.72 (2.36-3.09)
2.41 (2.11-2.71)
2.37 (1.98-2.76)
1.96 (1.71-2.2)
2.09 (1.83-2.35)
-0.137 -0.138, -0.136
<.01
-0.109 -0.11, -0.108
<.01
3.1 (2.51-3.69) 2.18 (0.93-3.44)
2.77 (2.32-3.22) 3.09 (0.9-5.27)
3.13 (2.69-3.55) 5.05 (2.93-7.16)
2.98 (2.57-3.37) 2.58 (1.47-3.7)
2.95 (2.53-3.37) 1.83 (0.96-2.7)
3.1 (2.67-3.54) 1.72 (1.15-2.3)
2.66 (2.3-3.03) 1.79 (1.28-3.3)
2.41 (2.09-2.73) 2.27 (1.15-3.4)
2.02 (1.75-2.3) 1.78 (1.26-2.29)
2.24 (1.94-2.53) 1.72 (1.18-2.27)
-0.101 -0.102, -0.1 -0.117 -0.124, -0.11
<.01
-0.112 -0.113, -0.111 -0.081 -0.088, -0.074
<.01
3.47 (2.56-4.37) 2.05 (1.41-2.69) 3.67 (2.29-5.05)
3.62 (2.81-4.43) 2.42 (1.80-3.03) 2.01 (1.27-2.74)
4.19 (3.46-4.91) 2.89 (2.35-3.43) 2.47 (1.63-3.31)
3.49 (2.79-4.19) 2.86 (2.17-3.55) 2.4 (1.88-2.91)
3.44 (2.71-4.17) 3.4 (2.63-4.17) 1.68 (1.27-2.09)
3.29 (2.53-4.04) 3.47 (2.79-4.14) 1.7 (1.32-2.09)
2.71 (2.1-3.31) 2.87 (2.19-3.54) 1.9 (1.54-2.27)
2.77 (1.74-3.8) 2.48 (2.01-2.95) 1.99 (1.53-2.46)
2.31 (1.81-2.81) 2.2 (1.71-2.68) 1.52 (1.22-1.83)
2.59 (1.98-3.19) 2.06 (1.67-2.45) 1.73 (1.36-2.1)
-0.156 -0.16, -0.152 -0.356 -0.36, -0.352 -0.113 -0.116, -0.11
<.01
-0.143 -0.146, -0.14 -0.045 -0.049, -0.041 -0.088 -0.091, -0.085
<.01
1.77 (1.05-2.5) 3.22 (2.3-4.14) 3.66 (2.68-4.63)
2.52 (1.73-3.32) 2.77 (1.99-3.56) 3.09 (2.35-3.84)
3.57 (2.55-4.58) 3.34 (2.75-3.94) 2.98 (2.16-3.80)
2.9 (2.12-3.43) 3.02 (2.58-3.63) 2.84 (2.0-3.67)
2.87 (2.07-3.68) 2.57 (2.11-3.04) 2.78 (2.08-3.49)
2.77 (2.04-3.49) 2.66 (2.19-3.14) 2.75 (2.06-3.45)
2.42 (1.88-2.95) 2.55 (2.09-3.0) 2.22 (1.6-2.85)
2.44 (1.58-3.3) 2.26 (1.81-2.72) 2.43 (1.87-2.98)
1.95 (1.51-2.4) 2.05 (1.69-2.4) 1.82 (1.34-2.31)
1.72 (1.29-2.15) 2.44 (2.1-2.78) 2.21 (1.58-2.85)
-0.079 -0.083, -0.075 -0.12 -0.123, -0.117 -0.13 -0.134, -0.126
.1
-0.064 -0.068, -0.06 -0.103 -0.106, -0.1 -0.156 -0.16, -0.152
.16
2.92 (1.72-4.12) 3.30 (2.62-3.97) 4.04 (0.33-7.76) 2.23 (0.69-3.76) 2.0 (0.16-3.85)
2.9 (1.84-3.96) 3.23 (2.54-3.92) 2.04 (0.92-3.16) 2.52 (1.13-3.91) 2.05 (0.75-3.35)
3.21 (2.41-4.01) 3.58 (2.82-4.33) 2.75 (1.69-3.81) 3.51 (2.02-4.99) 2.66 (1.56-3.75)
3.71 (2.7-4.71) 2.99 (2.47-3.51) 2.03 (1.36-2.7) 2.28 (1.45-3.11) 3.82 (1.48-6.15)
2.9 (2.09-3.71) 3.08 (2.45-3.71) 2.57 (1.33-3.81) 1.95 (1.14-2.77) 2.55 (1.06-4.04)
2.91 (1.99-3.83) 2.69 (2.16-3.22) 2.79 (1.27-4.3) 2.71 (1.66-3.77) 2.57 (1.75-3.4)
2.24 (1.5-2.98) 2.65 (2.17-3.12) 1.81 (1.16-2.47) 2.42 (1.56-3.29) 2.54 (1.51-3.57)
1.96 (1.40-2.53) 2.83 (1.98-3.67) 2.26 (1.27-3.26) 2.39 (1.68-3.1) 1.73 (1.11-2.36)
1.76 (1.14-2.37) 2.35 (1.94-2.76) 1.49 (0.98-2.01) 1.62 (0.93-2.30) 1.88 (1.27-2.50)
1.57 (1.07-2.07) 2.32 (1.84-2.79) 2.19 (1.46-2.93) 2.1 (1.45-2.76) 2.09 (1.42-2.76)
-0.191 -0.197, -0.185 -0.121 -0.124, -0.118 -0.108 -0.117, -0.099 -0.024 -0.032, -0.016 -0.075 -0.084, -0.066
<.01
2.62 (0.29-4.94) 3.02 (2.46-3.59)
2.79 (1.27-4.32) 2.8 (2.33-3.27)
3.18 (2.04-4.33) 3.31 (2.84-3.78)
2.92 (1.03-4.8) 2.93 (2.55-3.31)
2.33 (1.18-3.49) 2.81 (2.41-3.22)
3.42 (2.34-4.51) 2.59 (2.2-2.97)
2.61 (1.57-3.64) 2.37 (2.07-2.67)
2.56 (1.82-3.21) 2.33 (1.87-2.78)
1.63 (1.25-2.02) 2.08 (1.78-2.38)
1.92 (1.51-2.34) 2.16 (1.83-2.49)
-0.141 -0.148, -0.134 -0.11 -0.112, -0.108
<.01
.07
.34 <.01
<.01 <.01
<.01 .08 .66 .17
<.01
.16
.26 <.01
<.01 <.01
-0.172 -0.178, -0.166 -0.099 -0.102, -0.096 -0.097 -0.106, -0.088 -0.030 -0.037, -0.023 -0.086 -0.094, -0.079
<.01
-0.134 -0.141, -0.127 -0.105 -0.107, -0.103
.01
<.01 .13 .56 .07
<.01
CI, confidence interval; ICU, intensive care unit; MCICU, medical combined intensive care unit; MICU, medical intensive care unit; NSICU, neurosurgical intensive care unit; SCICU, surgical combined intensive care unit; SICU, surgical intensive care unit. *Number of central line−associated bloodstream infections/Number of central line-days £ 1,000. y Rates were based on the number of cases and the number at risk in the given year and the preceding year (1-year moving average). z The analysis was adjusted for the organizational and institutional characteristics of the hospitals and ICUs, such as the hospital location, total number of beds in the hospital and ICU, type of ICU, the number of infectious disease professionals, and whether the participating hospital was a university-affiliated hospital. x P values were calculated using a generalized autoregressive moving average linear model unless otherwise noted. k Kangwon-do/Gyeonggi-do/Incheon. { Central/South.
ARTICLE IN PRESS
Metropolitan areas near Seoul
k
2008 (95% CI)
x
E.J. Kim et al. / American Journal of Infection Control 00 (2019) 1−5
Location of hospitals Seoul
2007 (95% CI)
Adjusted modelz
Unadjusted model
ARTICLE IN PRESS E.J. Kim et al. / American Journal of Infection Control 00 (2019) 1−5
infection rate in time-critical situations in which zero-tolerance is possible. In the NHSN report, the pooled mean CLABSI rate for MICUs/SICUs of major teaching hospitals was 1.2 per 1,000 patients-days.21 Additional intervention efforts, such as applying a proven bundle in addition to surveillance, may be necessary in the KONIS. According to a pilot study by Choe et al22 in 2013 that investigated interventions for CLABSI prevention in 15 hospitals and 35 ICUs in South Korea, all ICUs had documented guidelines for the prevention of CLABSI, conducted surveillance, and had a hand hygiene promotion program. However, of these, only 19 (54%) ICUs provided regular education programs for CLABSI prevention and 15 (43%) ICUs accessed adherence to guidelines using a central-line insertion checklist. Twentynine (83%) ICUs used a sterile full body drape during insertion practice, and 3 (8%) ICUs used chlorhexidine preparation with alcohol for an insertion skin preparation.22 Previous studies have already demonstrated the effectiveness of interventions including a bundle approach and/or hand hygiene, which are cost-effective and easy methods of CLABSI prevention.23,24 In domestic studies, it has been demonstrated that a hand hygiene campaign and antibiotic stewardship program can lead to a significant reduction in methicillin-resistant Staphylococcus aureus bacteremia incidence by 33%.25,26 Therefore, it is expected that implementation of central-line bundles has the potential to reduce the incidence of CLABSI. This study has several limitations. First, smaller-sized hospitals with <300 beds did not participate in the KONIS. Second, only 61.8% (107 of 173) of hospitals in South Korea participated in the KONIS. Third, additional indicators are needed to correct for the hospitals’ disease severity. CONCLUSIONS We found a significant reduction in CLABSI rates over the last 10 years in South Korea that might be associated with participation in the KONIS. We expect that the rate of CLABSI can be reduced by encouraging more hospitals to participate in the KONIS, and by improved policy support for hospitals that lack the infection control resources. Acknowledgements The authors thank the participants of the Korean National Healthcare-associated Infections Surveillance System (KONIS) and their associated staff for their cooperation in this study. The authors would like to gratefully acknowledge all other steering members of the KONIS.* *Other steering members of the KONIS are (alphabetical order): Hyo Youl Kim, Young Sam Kim, Young Hwan Kim, Tae Hyong Kim, Hong Bin Kim, Keon-Woong Moon, Sun Hee Park, Young Uh, Byung Wook Eun, Mi Suk Lee, Sang-Oh Lee, Jun Yong Choi, Pyoeng Gyun Choe, Ki-Ho Hong, So-Yeon Yoo, Jin-Hong Yoo, and Ji-youn Choi. SUPPLEMENTARY MATERIALS Supplementary material associated with this article can be found in the online version at doi:10.1016/j.ajic.2019.07.020. References 1. Centers for Disease Control and Prevention, Guidelines for the prevention of intravascular catheter-related infections, 2011. Available from: https://www.cdc.gov/ hai/pdfs/bsi-guidelines-2011.pdf. Accessed July 8, 2018. 2. Velasquez Reyes DC, Bloomer M, Morphet J. Prevention of central venous line associated bloodstream infections in adult intensive care units: a systematic review. Intensive Crit Care Nurs 2017;43:12-22.
5
3. Lower HL, Eriksen HM, Aavitsland P, Skjeldestad FE. Methodology of the Norwegian Surveillance System for Healthcare-Associated Infections: the value of a mandatory system, automated data collection, and active postdischarge surveillance. Am J Infect Control 2013;41:591-6. 4. Kwak YG, Lee SO, Kim HY, Kim YK, Park ES, Jin HY, et al. Risk factors for deviceassociated infection related to organisational characteristics of intensive care units: findings from the Korean Nosocomial Infections Surveillance System. J Hosp Infect 2010;75:195-9. 5. Choi JY, Kwak YG, Yoo H, Lee SO, Kim HB, Han SH, et al. Trends in the incidence rate of device-associated infections in intensive care units after the establishment of the Korean Nosocomial Infections Surveillance System. J Hosp Infect 2015;91:28-34. 6. Haley RW, Culver DH, White JW, Morgan WM, Emori TG, Munn VP, et al. The efficacy of infection surveillance and control programs in preventing nosocomial infections in US hospitals. Am J Epidemiol 1985;121:182-205. 7. Horan TC, Andrus M, Dudeck MA. CDC/NHSN surveillance definition of health careassociated infection and criteria for specific types of infections in the acute care setting. Am J Infect Control 2008;36:309-32. 8. Kwak YG, Choi JY, Yoo HM, Lee SO, Kim HB, Han SH, et al. Validation of the Korean National Healthcare-associated Infections Surveillance System (KONIS): an intensive care unit module report. J Hosp Infect 2017;96:377-84. 9. Mayer-Davis EJ, Lawrence JM, Dabelea D, Divers J, Isom S, Dolan L, et al. Incidence trends of type 1 and type 2 diabetes among youths, 2002-2012. N Engl J Med 2017;376:1419-29. 10. Marsteller JA, Hsu YJ, Weeks K. Evaluating the impact of mandatory public reporting on participation and performance in a program to reduce central line-associated bloodstream infections: evidence from a national patient safety collaborative. Am J Infect Control 2014;42(10 Suppl):209-15. 11. Gastmeier P, Geffers C, Brandt C, Zuschneid I, Sohr D, Schwab F, et al. Effectiveness of a nationwide nosocomial infection surveillance system for reducing nosocomial infections. J Hosp Infect 2006;64:16-22. 12. KONIS Manual 2016. Seoul: Korean Society for Healthcare-associated Infection Control and Prevention; 2016. 13. Kim EJ, Kwak YG, Park SH, Kim SR, Shin MJ, Yoo HM, et al. Trends in device utilization ratios in intensive care units over 10-year period in South Korea: device utilization ratio as a new aspect of surveillance. J Hosp Infect 2018;100:e169-77. 14. Warren DK, Quadir WW, Hollenbeak CS, Elward AM, Cox MJ, Fraser VJ. Attributable cost of catheter-associated bloodstream infections among intensive care patients in a nonteaching hospital. Crit Care Med 2006;34:2084-9. 15. O’Grady NP, Alexander M, Burns LA, Dellinger EP, Garland J, Heard SO, et al. Guidelines for the prevention of intravascular catheter-related infections. Clin Infect Dis 2011;52:e162-93. 16. Blot SI, Depuydt P, Annemans L, Benoit D, Hoste E, De Waele JJ, et al. Clinical and economic outcomes in critically ill patients with nosocomial catheter-related bloodstream infections. Clin Infect Dis 2005;41:1591-8. 17. Yoon YK, Lee SE, Seo BS, Kim HJ, Kim JH, Yang KS, et al. Current status of personnel and infrastructure resources for infection prevention and control programs in the Republic of Korea: a national survey. Am J Infect Control 2016;44:e189-93. 18. Taiwan Centers for Disease Control. Taiwan nosocomial infections surveillance system. Available from: https://www.cdc.gov.tw/english/info.aspx?treeid=00ED75D6C887BB27&nowtreeid=F0131176AA46D5DB&tid=1A8C498AF5F8AF5D. Accessed July 8, 2018. 19. Balkhy HH, El-Saed A, Al-Abri SS, Alsalman J, Alansari H, Al Maskari Z, et al. Rates of central line-associated bloodstream infection in tertiary care hospitals in 3 Arabian gulf countries: 6-year surveillance study. Am J Infect Control 2017;45:e49-51. 20. Rosenthal VD, Maki DG, Jamulitrat S, Medeiros EA, Todi SK, Gomez DY, et al. International Nosocomial Infection Control Consortium (INICC) report, data summary for 2003-2008, issued June 2009. Am J Infect Control 2010;38: 95-104.e2. 21. Dudeck MA, Weiner LM, Allen-Bridson K, Malpiedi PJ, Peterson KD, Pollock DA, et al. National Healthcare Safety Network (NHSN) report, data summary for 2012, device-associated module. Am J Infect Control 2013;41:1148-66. 22. Choe PG, Shin HY, Shin MJ, Song KH, Kim ES, Jin HY, et al. P003: Current status of infection control practice for prevent of central venous catheter-associated bloodstream infection in Korea. Antimicrob Resist Infect Control 2013;2 (Suppl 1):P3. 23. Johnson L, Grueber S, Schlotzhauer C, Phillips E, Bullock P, Basnett J, et al. A multifactorial action plan improves hand hygiene adherence and significantly reduces central line-associated bloodstream infections. Am J Infect Control 2014;42:1146-51. 24. Ista E, van der Hoven B, Kornelisse RF, van der Starre C, Vos MC, Boersma E, et al. Effectiveness of insertion and maintenance bundles to prevent central-line-associated bloodstream infections in critically ill patients of all ages: a systematic review and meta-analysis. Lancet Infect Dis 2016;16:724-34. 25. Chun JY, Seo HK, Kim MK, Shin MJ, Kim SY, Kim M, et al. Impact of a hand hygiene campaign in a tertiary hospital in South Korea on the rate of hospital-onset methicillin-resistant Staphylococcus aureus bacteremia and economic evaluation of the campaign. Am J Infect Control 2016;44:1486-91. 26. Kim YC, Kim MH, Song JE, Ahn JY, Oh DH, Kweon OM, et al. Trend of methicillinresistant Staphylococcus aureus (MRSA) bacteremia in an institution with a high rate of MRSA after the reinforcement of antibiotic stewardship and hand hygiene. Am J Infect Control 2013;41:e39-43.
Contents lists available at ScienceDirect
American Journal of Infection Control journal homepage: www.ajicjournal.org
Major Article
Ten-year surveillance of central line−associated bloodstream infections in South Korea: Surveillance not enough, action needed Eun Jin Kim MD a, So Young Kang PhD b, Yee Gyung Kwak MD, PhD c, Sung Ran Kim RN d, Myoung Jin Shin RN e, Hyeon Mi Yoo RN f, Su Ha Han RN g, Dong Wook Kim PhD h, Young Hwa Choi MD, PhD a,*, the Steering Committee of KONIS a
Department of Infectious Diseases, Ajou University School of Medicine, Suwon, South Korea Office of Biostatistics, Institute of Medical Sciences, Ajou University School of Medicine, Suwon, South Korea c Department of Internal Medicine, Inje University Ilsan Paik Hospital, Goyang, South Korea d Infection Control Office, Korea University Guro Hospital, Seoul, South Korea e Infection Control Office, Seoul National University Bundang Hospital, Seongnam, South Korea f Infection Control Office, Inje University Sanggye Paik Hospital, Seoul, South Korea g Department of Nursing, Soonchunhyang University College of Medicine, Cheonan, South Korea h Department of Policy Research Affairs, National Health Insurance Service Ilsan Hospital, Goyang, South Korea b
Key Words: Intensive care units Healthcare-associated infections Blood stream infections Korean National Healthcare-associated Infections Surveillance System (KONIS)
Background: Central line−associated bloodstream infections (CLABSIs) are preventable health care−associated infections that can lead to increased mortality. Therefore, we investigated trends in CLABSI rates, and the factors associated with changing trends over a 10-year period using the Korean National Healthcareassociated Infections Surveillance System (KONIS). Methods: We investigated annual CLABSI rates from 2006 to 2015 in 190 KONIS-participating intensive care units (ICUs) from 107 participating hospitals. We collected data associated with hospital and ICU characteristics and analyzed trends using generalized autoregressive moving average models. Results: The CLABSI pooled mean rate decreased from 3.40 in 2006 to 2.20 in 2015 (per 1,000 catheter-days). The trend analysis also showed a significant decreasing trend in CLABSI rates in unadjusted models (annual increase, −0.137; P < .001). After adjusting for hospital and ICU characteristics, significant decreasing trends were identified (annual increase, −0.109; P < .001). However, there were no significant changes in subgroups with non-university-affiliated hospitals, hospitals in metropolitan areas near Seoul, small hospitals (300-699 beds), or surgical ICUs. Conclusions: In South Korea, CLABSI rates have shown significant reductions in the past 10 years with participation in the KONIS. However, CLABSI rates may be reduced by encouraging more hospitals to participate in the KONIS and by improved policy support for hospitals lacking infection control resources. © 2019 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
A central line−associated bloodstream infection (CLABSI) is a laboratory-confirmed bloodstream infection (BSI) in a patient who has had a central line within the 48 hours prior to BSI development, which is unrelated to an infection at another site.1,2 Although these infections are preventable, it is well-known that CLABSI increases * Address correspondence to Young Hwa Choi, MD, PhD, Department of Infectious Diseases, Ajou University School of Medicine, 164, World cup-ro, Yeongtong-gu, 16499 Suwon-si, Gyeonggi-do, South Korea. E-mail address: [email protected] (Y.H. Choi). Funding/support: This work was supported by the Research Program [2016E2300200] funded by the Korea Center for Disease Control and Prevention, 2016. Conflicts of interest: None to report.
mortality and morbidity, and also leads to increased medical costs.3 Therefore, in South Korea, we have continuously monitored health care−associated infections (HAIs), including CLABSI, in intensive care units (ICUs) through the Korean National Healthcare-associated Infections Surveillance System (KONIS) program, run by the Korea Center for Disease Control and Prevention and the Korean Society for Healthcare-associated Infection Control and Prevention. The experience of the National Healthcare Safety Network (NHSN) in the United States was taken into consideration when developing the KONIS, and this system focuses on the surveillance and prevention of device-associated infections (DAIs) in adult patients in ICUs.4,5
https://doi.org/10.1016/j.ajic.2019.07.020 0196-6553/© 2019 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
ARTICLE IN PRESS 2
E.J. Kim et al. / American Journal of Infection Control 00 (2019) 1−5
A trend analysis was performed based on 10 years of observations from the KONIS, which was established in 2006. In particular, we aimed to investigate if this continuous surveillance system helped to reduce the trend in the incidence of HAIs, similar to a study on the efficacy of the nosocomial infection control (SENIC) project, and we examined the effect of surveillance by analyzing trends in incidence according to the characteristics of each hospital and ICU.6 We also evaluated year-wise time trends of CLABSI rates in ICUs that continuously participated in the KONIS from 2007-2015. METHODS KONIS system The KONIS involved prospective surveillance of HAI, including CLABSI rates and central line-device use ratios, in participating ICUs between 2006 and 2015. The definitions of CLABSI and central linedevice utilization ratios were standardized and based on those of the Centers for Disease Control of Prevention/NHSN system.7 Investigators were provided with a manual and training tool containing a detailed description of how surveillance must be performed, and complete surveillance forms to ensure standardized implementation. In addition, we conducted regular training twice yearly, and all data were validated externally.8 Surveillance Trained infection preventionists (IPs) collected data from ICU patients in participating hospitals. All patients who stayed in the ICU for >2 days were included in the surveillance and were followed up from admission until discharge or death. After ICU discharge, patients were followed up for infection for an additional 2 days. Device-associated HAI rates were calculated as the number of infections per 1,000 device-days, and device use was calculated as a ratio of total devicedays to total patient-days. The pooled incidences of DAIs and device utilization ratios were calculated for each year of participation. We also collected data on the organizational and institutional characteristics of the included hospitals and ICUs, such as hospital location; total number of beds in the hospital and ICU; type of ICU; the number of ICU nursing staff, IPs, and infectious disease professionals; and whether the hospital was a major teaching hospital, a private hospital, or a university-affiliated hospital. A major teaching hospital was defined as a hospital with programs for medical students and postgraduate medical training (ie, residency and/or fellowships). Hospitals were stratified by the number of beds: 300-699, 700-899, and ≥900. The types of ICUs in this study were as follows: medical ICU (MICU), medical combined ICU (MCICU), surgical combined ICU (SCICU), surgical ICU (SICU), and neurosurgical ICU (NSICU). The ICUs were classified according to the type of patients involved in their care, according to the average department of ICU. An MICU was defined as having >80% of internal medicine patients alone. An SICU and NSICU were defined as having >80% of general surgery and neurosurgery patients, respectively. Other cases were categorized as combined ICU, MCICU, and SCICU. Consecutive participating hospitals Although the survey was initiated in September 2006, the duration in 2006 was only half a year. Since 2007, there has been greater participation, and the organization of the conference of the Korean Society for Healthcare-associated Infection Control and Prevention and KONIS Board has improved. From 2007, we analyzed only hospitals that participated every year until 2015. These hospitals will be able to accurately represent the benefits of KONIS’ continued involvement.
Statistical analyses Analysis of trends was performed using the generalized autoregressive moving average (GARMA) to account for serial correlation.9 Trends that were adjusted for organizational and institutional characteristics of the hospitals and ICUs (such as hospital location, total number of beds in the hospital and ICU, type of ICU, the number of IPs and infectious disease professionals, and whether the hospital was a university-affiliated hospital), and unadjusted trends in CLABSI rates were estimated using a GARMA model. Epi Info version 7 (Centers for Disease Control of Prevention, Atlanta, GA) and SAS statistical program version 9.4 (SAS Institute Inc, Cary, NC) were used to conduct data analyses. Statistical significance was considered as P <.05. Ethical declaration This is a study using information disclosed to the general public as national data, and institutional review board approval was exempted from studies that do not collect or record personally identifiable information. RESULTS During the decade of surveillance, linear mixed regression models indicated that CLABSI rates significantly decreased from 3.40 in 2006 to 2.20 in 2015 (per 1,000 catheter-days, F = 14.17; P < .001) (Fig 1A). The trend analysis using GARMA also showed a significant decrease in the rate of CLABSI. In the unadjusted models, a significant downward trend in the rate of CLABSI was observed overall (from 2.99 per 1,000 catheter-days in 2006 to 2.09 per 1,000 catheter-days in 2015; annual increase, −0.137; P < .001). Depending on the type of hospital and ICU, subgroup analysis revealed an almost significant decreasing trend. However, there were no significant changes noted for subgroups of hospitals that were non-university-affiliated, or that were located in metropolitan areas near and around Seoul. In addition, the trend was not significant among the subgroup including small hospitals with 300-699 beds. When classified by ICU characteristics, there was no significant decreasing trend in SICU series as follows SCICU, SICU, and NSICU; however, there was a significant decrease in MICUs. In Supplementary Table S1, the number of participating ICUs that changed annually during the study period is shown. After adjustment for location, hospital size, university-affiliated hospitals, type of ICU, and number of infection specialists, significant decreases in trends of the rate of CLABSI were identified in all participating hospitals (annual increase, −0.109; P < .001) (Fig 1B). After subgroup analysis, the results were similar to those before adjustment. There were no significant changes in trends for subgroups with non-university-affiliated hospitals, hospitals in metropolitan areas near and around Seoul, small hospitals with between 300 and 699 beds, and SICUs (Table 1). Since 2006, analysis of the trend in CLABSI incidence in consecutive participating hospitals, which was consistently recorded from 2007-2015, showed a significant decline in both unadjusted (annual increase, −0.119; P < .001) and adjusted models (annual increase, −0.119; P < .001). Likewise, in subgroup analysis, there was no significant decreasing trend in non-university-affiliated hospitals, metropolitan hospitals in the suburbs of Seoul, small hospitals with 300699 beds, and SICUs (Supplementary Table S2). DISCUSSION In the past decade, CLABSI rates have shown significant reductions using trend analysis in South Korea. Depending on the type of hospital and ICU, subgroup analysis also revealed an almost significant decreasing trend. Therefore, the national surveillance program of
ARTICLE IN PRESS E.J. Kim et al. / American Journal of Infection Control 00 (2019) 1−5
3
Fig 1. Trends in central line−associated bloodstream infection (CLABSI) rates in intensive care units between 2006 and 2015. (A) A scatter plot is presented with the horizontal line representing the trend. The device-associated infection rates (per 1,000 device-days) on the y-axis were calculated as the total number of infections per 1,000 device-days and were multiplied by 1,000 (F = 14.17; P < .001). (B) Model-adjusted CLABSI rate estimates.
10 years was effective in South Korea. As already demonstrated in the SENIC study, national surveillance has a positive impact on the prevention of HAI.6 Several studies have also identified positive effects on the reduction in CLABSI rate by applying a national surveillance program.10,11 Under the leadership of the government, South Korea implemented the national surveillance system in cooperation with the Korean Society of Infectious Disease in 2006. From July 2006, there were 76 participating ICUs from 44 hospitals nationwide that started monitoring HAI. In 2006, we implemented standards and recruited participating hospitals; the unified criteria and methods required for the monitoring of HAIs in ICUs were summarized in the 2006 KONIS manual and were revised biannually.12 In 2007, the number of hospitals participating in the KONIS increased and a new surgical site infection module was added. To improve the accuracy of the KONIS data, a “validation” method was developed and applied in 2008. External validation and guidance manual revision and education were performed every 2 years.8,13 Hospitals with >400 beds were invited to participate at the beginning of 2006, with 44 (33.8%) of 130 hospitals participating nationwide. Since 2010, hospitals with >300 beds have been able to participate, and 72 hospitals (72 of 161, 44.7%) participated in 2010. In 2015, 95 hospitals participated, and the participation rate is increasing every year. It was 55.2% (95 of 172) of all hospitals that can participate in South Korea, which can ensure the generality of this data. In addition, standardization and regular education regarding ICU infection monitoring was consistently performed. Comparison between participating hospitals was made possible, which led to improvements in infection control quality, and as a result, DAI decreased. Of DAIs, CLABSI is an independent risk factor for increased medical costs and prolonged hospitalization period. According to the KONIS data, CLABSI accounts for >85% of total BSIs every year in the ICUs. The mortality rate of CLABSI is known to be approximately 3%, with severe infection approximately 25%. Moreover, it is estimated that the average cost of medical care for CLABSI is an additional $19,633$28,508 per patient.14 Intravascular catheters are used for various purposes, including dialysis, nutrition, drug administration, and intravascular procedures, and use is increasing in the ICU.14-16 Therefore, the reduction in CLABSI after an infection control program is an important issue, and significant effort is required.
As the KONIS used a unified definition of CLABSI and surveillance methods, it was possible to compare infection rates according to the size and area of each hospital. However, interventions, such as using a bundle approach or suggesting guidelines for CLABSI prevention, were not provided. Instead, through constant participation in the KONIS, there was regular lecture-based training on topics such as basic HAI concepts to surveillance methods. Continuous participation has enabled comparison with other hospitals to motivate hospitals to manage their infection rate. This is likely to have contributed to the success of DAI reduction including CLABSI. Furthermore, as shown in Supplementary Table S2, subgroup analysis of hospitals that participated in the KONIS every year since 2007 showed a significant decrease in CLABSI rate. This shows that the KONIS had a positive impact on the infection rate through continuous surveillance. In other respects, subgroup analysis did not show a declining trend for hospitals in areas outside of Seoul, small hospitals, or surgical or non-university hospitals. This suggests that infection control resources are mainly concentrated in hospitals in Seoul, MICUs, and university hospitals. In a previous study, larger hospitals and university-affiliated hospitals were found to have better employment status of infection specialists and hand hygiene resources.17 In the end, it was estimated that the infection rate in smaller hospitals was more likely to reflect the lack of infection control personnel and infection control resources. Thus, with further research, it would be beneficial to investigate whether indicators of improvement change with more intensive support and management in small hospitals. In particular, efforts will need to be made to employ an infectious disease specialist in addition to other efforts to reduce CLABSI after surgery in hospitals beyond the region of Seoul. Numerous studies have reported the effect of surveillance programs in other countries. In Taiwan, the incidence density of HAI decreased by 46.2% from 9.3 episodes to 5.0 episodes per 1,000 patients-day after implementing a national surveillance system from 2006-2015.18 In several studies conducted in both developing and developed countries, participation in national surveillance has been shown to reduce CLABSI by 25%-33%.11,19,20 Compared with other countries, the CLABSI rate is considered to be higher in South Korea than in high-income countries such as the United States, Australia, and Canada, whereas the rate is similar in Northeast Asia (eg, Japan and Taiwan). Additional action is now required to further reduce the
4
Table 1 Central line−associated bloodstream infection rates* in intensive care units during 2006-2015, calculated with the use of 1-year moving averagesy Year 2006 (95% CI)
Subgroup
All participants University-affiliated hospitals Yes No
Southern-metropolitan area{ Size of hospitals 300-699 beds 700-899 beds ≥900 beds Type of ICU MCICU MICU NSICU SCICU SICU Beds per an infection specialist <300 beds ≥300 beds
2009 (95% CI)
2010 (95% CI)
2011 (95% CI)
2012 (95% CI)
2013 (95% CI)
2014 (95% CI)
2015 (95% CI)
Annual increase, 95% CI
P value
Annual increase, 95% CI
P valuex
2.99 (2.46-3.52)
2.8 (2.36-3.24)
3.29 (2.86-3.72)
2.93 (2.56-3.3)
2.74 (2.36-3.12)
2.72 (2.36-3.09)
2.41 (2.11-2.71)
2.37 (1.98-2.76)
1.96 (1.71-2.2)
2.09 (1.83-2.35)
-0.137 -0.138, -0.136
<.01
-0.109 -0.11, -0.108
<.01
3.1 (2.51-3.69) 2.18 (0.93-3.44)
2.77 (2.32-3.22) 3.09 (0.9-5.27)
3.13 (2.69-3.55) 5.05 (2.93-7.16)
2.98 (2.57-3.37) 2.58 (1.47-3.7)
2.95 (2.53-3.37) 1.83 (0.96-2.7)
3.1 (2.67-3.54) 1.72 (1.15-2.3)
2.66 (2.3-3.03) 1.79 (1.28-3.3)
2.41 (2.09-2.73) 2.27 (1.15-3.4)
2.02 (1.75-2.3) 1.78 (1.26-2.29)
2.24 (1.94-2.53) 1.72 (1.18-2.27)
-0.101 -0.102, -0.1 -0.117 -0.124, -0.11
<.01
-0.112 -0.113, -0.111 -0.081 -0.088, -0.074
<.01
3.47 (2.56-4.37) 2.05 (1.41-2.69) 3.67 (2.29-5.05)
3.62 (2.81-4.43) 2.42 (1.80-3.03) 2.01 (1.27-2.74)
4.19 (3.46-4.91) 2.89 (2.35-3.43) 2.47 (1.63-3.31)
3.49 (2.79-4.19) 2.86 (2.17-3.55) 2.4 (1.88-2.91)
3.44 (2.71-4.17) 3.4 (2.63-4.17) 1.68 (1.27-2.09)
3.29 (2.53-4.04) 3.47 (2.79-4.14) 1.7 (1.32-2.09)
2.71 (2.1-3.31) 2.87 (2.19-3.54) 1.9 (1.54-2.27)
2.77 (1.74-3.8) 2.48 (2.01-2.95) 1.99 (1.53-2.46)
2.31 (1.81-2.81) 2.2 (1.71-2.68) 1.52 (1.22-1.83)
2.59 (1.98-3.19) 2.06 (1.67-2.45) 1.73 (1.36-2.1)
-0.156 -0.16, -0.152 -0.356 -0.36, -0.352 -0.113 -0.116, -0.11
<.01
-0.143 -0.146, -0.14 -0.045 -0.049, -0.041 -0.088 -0.091, -0.085
<.01
1.77 (1.05-2.5) 3.22 (2.3-4.14) 3.66 (2.68-4.63)
2.52 (1.73-3.32) 2.77 (1.99-3.56) 3.09 (2.35-3.84)
3.57 (2.55-4.58) 3.34 (2.75-3.94) 2.98 (2.16-3.80)
2.9 (2.12-3.43) 3.02 (2.58-3.63) 2.84 (2.0-3.67)
2.87 (2.07-3.68) 2.57 (2.11-3.04) 2.78 (2.08-3.49)
2.77 (2.04-3.49) 2.66 (2.19-3.14) 2.75 (2.06-3.45)
2.42 (1.88-2.95) 2.55 (2.09-3.0) 2.22 (1.6-2.85)
2.44 (1.58-3.3) 2.26 (1.81-2.72) 2.43 (1.87-2.98)
1.95 (1.51-2.4) 2.05 (1.69-2.4) 1.82 (1.34-2.31)
1.72 (1.29-2.15) 2.44 (2.1-2.78) 2.21 (1.58-2.85)
-0.079 -0.083, -0.075 -0.12 -0.123, -0.117 -0.13 -0.134, -0.126
.1
-0.064 -0.068, -0.06 -0.103 -0.106, -0.1 -0.156 -0.16, -0.152
.16
2.92 (1.72-4.12) 3.30 (2.62-3.97) 4.04 (0.33-7.76) 2.23 (0.69-3.76) 2.0 (0.16-3.85)
2.9 (1.84-3.96) 3.23 (2.54-3.92) 2.04 (0.92-3.16) 2.52 (1.13-3.91) 2.05 (0.75-3.35)
3.21 (2.41-4.01) 3.58 (2.82-4.33) 2.75 (1.69-3.81) 3.51 (2.02-4.99) 2.66 (1.56-3.75)
3.71 (2.7-4.71) 2.99 (2.47-3.51) 2.03 (1.36-2.7) 2.28 (1.45-3.11) 3.82 (1.48-6.15)
2.9 (2.09-3.71) 3.08 (2.45-3.71) 2.57 (1.33-3.81) 1.95 (1.14-2.77) 2.55 (1.06-4.04)
2.91 (1.99-3.83) 2.69 (2.16-3.22) 2.79 (1.27-4.3) 2.71 (1.66-3.77) 2.57 (1.75-3.4)
2.24 (1.5-2.98) 2.65 (2.17-3.12) 1.81 (1.16-2.47) 2.42 (1.56-3.29) 2.54 (1.51-3.57)
1.96 (1.40-2.53) 2.83 (1.98-3.67) 2.26 (1.27-3.26) 2.39 (1.68-3.1) 1.73 (1.11-2.36)
1.76 (1.14-2.37) 2.35 (1.94-2.76) 1.49 (0.98-2.01) 1.62 (0.93-2.30) 1.88 (1.27-2.50)
1.57 (1.07-2.07) 2.32 (1.84-2.79) 2.19 (1.46-2.93) 2.1 (1.45-2.76) 2.09 (1.42-2.76)
-0.191 -0.197, -0.185 -0.121 -0.124, -0.118 -0.108 -0.117, -0.099 -0.024 -0.032, -0.016 -0.075 -0.084, -0.066
<.01
2.62 (0.29-4.94) 3.02 (2.46-3.59)
2.79 (1.27-4.32) 2.8 (2.33-3.27)
3.18 (2.04-4.33) 3.31 (2.84-3.78)
2.92 (1.03-4.8) 2.93 (2.55-3.31)
2.33 (1.18-3.49) 2.81 (2.41-3.22)
3.42 (2.34-4.51) 2.59 (2.2-2.97)
2.61 (1.57-3.64) 2.37 (2.07-2.67)
2.56 (1.82-3.21) 2.33 (1.87-2.78)
1.63 (1.25-2.02) 2.08 (1.78-2.38)
1.92 (1.51-2.34) 2.16 (1.83-2.49)
-0.141 -0.148, -0.134 -0.11 -0.112, -0.108
<.01
.07
.34 <.01
<.01 <.01
<.01 .08 .66 .17
<.01
.16
.26 <.01
<.01 <.01
-0.172 -0.178, -0.166 -0.099 -0.102, -0.096 -0.097 -0.106, -0.088 -0.030 -0.037, -0.023 -0.086 -0.094, -0.079
<.01
-0.134 -0.141, -0.127 -0.105 -0.107, -0.103
.01
<.01 .13 .56 .07
<.01
CI, confidence interval; ICU, intensive care unit; MCICU, medical combined intensive care unit; MICU, medical intensive care unit; NSICU, neurosurgical intensive care unit; SCICU, surgical combined intensive care unit; SICU, surgical intensive care unit. *Number of central line−associated bloodstream infections/Number of central line-days £ 1,000. y Rates were based on the number of cases and the number at risk in the given year and the preceding year (1-year moving average). z The analysis was adjusted for the organizational and institutional characteristics of the hospitals and ICUs, such as the hospital location, total number of beds in the hospital and ICU, type of ICU, the number of infectious disease professionals, and whether the participating hospital was a university-affiliated hospital. x P values were calculated using a generalized autoregressive moving average linear model unless otherwise noted. k Kangwon-do/Gyeonggi-do/Incheon. { Central/South.
ARTICLE IN PRESS
Metropolitan areas near Seoul
k
2008 (95% CI)
x
E.J. Kim et al. / American Journal of Infection Control 00 (2019) 1−5
Location of hospitals Seoul
2007 (95% CI)
Adjusted modelz
Unadjusted model
ARTICLE IN PRESS E.J. Kim et al. / American Journal of Infection Control 00 (2019) 1−5
infection rate in time-critical situations in which zero-tolerance is possible. In the NHSN report, the pooled mean CLABSI rate for MICUs/SICUs of major teaching hospitals was 1.2 per 1,000 patients-days.21 Additional intervention efforts, such as applying a proven bundle in addition to surveillance, may be necessary in the KONIS. According to a pilot study by Choe et al22 in 2013 that investigated interventions for CLABSI prevention in 15 hospitals and 35 ICUs in South Korea, all ICUs had documented guidelines for the prevention of CLABSI, conducted surveillance, and had a hand hygiene promotion program. However, of these, only 19 (54%) ICUs provided regular education programs for CLABSI prevention and 15 (43%) ICUs accessed adherence to guidelines using a central-line insertion checklist. Twentynine (83%) ICUs used a sterile full body drape during insertion practice, and 3 (8%) ICUs used chlorhexidine preparation with alcohol for an insertion skin preparation.22 Previous studies have already demonstrated the effectiveness of interventions including a bundle approach and/or hand hygiene, which are cost-effective and easy methods of CLABSI prevention.23,24 In domestic studies, it has been demonstrated that a hand hygiene campaign and antibiotic stewardship program can lead to a significant reduction in methicillin-resistant Staphylococcus aureus bacteremia incidence by 33%.25,26 Therefore, it is expected that implementation of central-line bundles has the potential to reduce the incidence of CLABSI. This study has several limitations. First, smaller-sized hospitals with <300 beds did not participate in the KONIS. Second, only 61.8% (107 of 173) of hospitals in South Korea participated in the KONIS. Third, additional indicators are needed to correct for the hospitals’ disease severity. CONCLUSIONS We found a significant reduction in CLABSI rates over the last 10 years in South Korea that might be associated with participation in the KONIS. We expect that the rate of CLABSI can be reduced by encouraging more hospitals to participate in the KONIS, and by improved policy support for hospitals that lack the infection control resources. Acknowledgements The authors thank the participants of the Korean National Healthcare-associated Infections Surveillance System (KONIS) and their associated staff for their cooperation in this study. The authors would like to gratefully acknowledge all other steering members of the KONIS.* *Other steering members of the KONIS are (alphabetical order): Hyo Youl Kim, Young Sam Kim, Young Hwan Kim, Tae Hyong Kim, Hong Bin Kim, Keon-Woong Moon, Sun Hee Park, Young Uh, Byung Wook Eun, Mi Suk Lee, Sang-Oh Lee, Jun Yong Choi, Pyoeng Gyun Choe, Ki-Ho Hong, So-Yeon Yoo, Jin-Hong Yoo, and Ji-youn Choi. SUPPLEMENTARY MATERIALS Supplementary material associated with this article can be found in the online version at doi:10.1016/j.ajic.2019.07.020. References 1. Centers for Disease Control and Prevention, Guidelines for the prevention of intravascular catheter-related infections, 2011. Available from: https://www.cdc.gov/ hai/pdfs/bsi-guidelines-2011.pdf. Accessed July 8, 2018. 2. Velasquez Reyes DC, Bloomer M, Morphet J. Prevention of central venous line associated bloodstream infections in adult intensive care units: a systematic review. Intensive Crit Care Nurs 2017;43:12-22.
5
3. Lower HL, Eriksen HM, Aavitsland P, Skjeldestad FE. Methodology of the Norwegian Surveillance System for Healthcare-Associated Infections: the value of a mandatory system, automated data collection, and active postdischarge surveillance. Am J Infect Control 2013;41:591-6. 4. Kwak YG, Lee SO, Kim HY, Kim YK, Park ES, Jin HY, et al. Risk factors for deviceassociated infection related to organisational characteristics of intensive care units: findings from the Korean Nosocomial Infections Surveillance System. J Hosp Infect 2010;75:195-9. 5. Choi JY, Kwak YG, Yoo H, Lee SO, Kim HB, Han SH, et al. Trends in the incidence rate of device-associated infections in intensive care units after the establishment of the Korean Nosocomial Infections Surveillance System. J Hosp Infect 2015;91:28-34. 6. Haley RW, Culver DH, White JW, Morgan WM, Emori TG, Munn VP, et al. The efficacy of infection surveillance and control programs in preventing nosocomial infections in US hospitals. Am J Epidemiol 1985;121:182-205. 7. Horan TC, Andrus M, Dudeck MA. CDC/NHSN surveillance definition of health careassociated infection and criteria for specific types of infections in the acute care setting. Am J Infect Control 2008;36:309-32. 8. Kwak YG, Choi JY, Yoo HM, Lee SO, Kim HB, Han SH, et al. Validation of the Korean National Healthcare-associated Infections Surveillance System (KONIS): an intensive care unit module report. J Hosp Infect 2017;96:377-84. 9. Mayer-Davis EJ, Lawrence JM, Dabelea D, Divers J, Isom S, Dolan L, et al. Incidence trends of type 1 and type 2 diabetes among youths, 2002-2012. N Engl J Med 2017;376:1419-29. 10. Marsteller JA, Hsu YJ, Weeks K. Evaluating the impact of mandatory public reporting on participation and performance in a program to reduce central line-associated bloodstream infections: evidence from a national patient safety collaborative. Am J Infect Control 2014;42(10 Suppl):209-15. 11. Gastmeier P, Geffers C, Brandt C, Zuschneid I, Sohr D, Schwab F, et al. Effectiveness of a nationwide nosocomial infection surveillance system for reducing nosocomial infections. J Hosp Infect 2006;64:16-22. 12. KONIS Manual 2016. Seoul: Korean Society for Healthcare-associated Infection Control and Prevention; 2016. 13. Kim EJ, Kwak YG, Park SH, Kim SR, Shin MJ, Yoo HM, et al. Trends in device utilization ratios in intensive care units over 10-year period in South Korea: device utilization ratio as a new aspect of surveillance. J Hosp Infect 2018;100:e169-77. 14. Warren DK, Quadir WW, Hollenbeak CS, Elward AM, Cox MJ, Fraser VJ. Attributable cost of catheter-associated bloodstream infections among intensive care patients in a nonteaching hospital. Crit Care Med 2006;34:2084-9. 15. O’Grady NP, Alexander M, Burns LA, Dellinger EP, Garland J, Heard SO, et al. Guidelines for the prevention of intravascular catheter-related infections. Clin Infect Dis 2011;52:e162-93. 16. Blot SI, Depuydt P, Annemans L, Benoit D, Hoste E, De Waele JJ, et al. Clinical and economic outcomes in critically ill patients with nosocomial catheter-related bloodstream infections. Clin Infect Dis 2005;41:1591-8. 17. Yoon YK, Lee SE, Seo BS, Kim HJ, Kim JH, Yang KS, et al. Current status of personnel and infrastructure resources for infection prevention and control programs in the Republic of Korea: a national survey. Am J Infect Control 2016;44:e189-93. 18. Taiwan Centers for Disease Control. Taiwan nosocomial infections surveillance system. Available from: https://www.cdc.gov.tw/english/info.aspx?treeid=00ED75D6C887BB27&nowtreeid=F0131176AA46D5DB&tid=1A8C498AF5F8AF5D. Accessed July 8, 2018. 19. Balkhy HH, El-Saed A, Al-Abri SS, Alsalman J, Alansari H, Al Maskari Z, et al. Rates of central line-associated bloodstream infection in tertiary care hospitals in 3 Arabian gulf countries: 6-year surveillance study. Am J Infect Control 2017;45:e49-51. 20. Rosenthal VD, Maki DG, Jamulitrat S, Medeiros EA, Todi SK, Gomez DY, et al. International Nosocomial Infection Control Consortium (INICC) report, data summary for 2003-2008, issued June 2009. Am J Infect Control 2010;38: 95-104.e2. 21. Dudeck MA, Weiner LM, Allen-Bridson K, Malpiedi PJ, Peterson KD, Pollock DA, et al. National Healthcare Safety Network (NHSN) report, data summary for 2012, device-associated module. Am J Infect Control 2013;41:1148-66. 22. Choe PG, Shin HY, Shin MJ, Song KH, Kim ES, Jin HY, et al. P003: Current status of infection control practice for prevent of central venous catheter-associated bloodstream infection in Korea. Antimicrob Resist Infect Control 2013;2 (Suppl 1):P3. 23. Johnson L, Grueber S, Schlotzhauer C, Phillips E, Bullock P, Basnett J, et al. A multifactorial action plan improves hand hygiene adherence and significantly reduces central line-associated bloodstream infections. Am J Infect Control 2014;42:1146-51. 24. Ista E, van der Hoven B, Kornelisse RF, van der Starre C, Vos MC, Boersma E, et al. Effectiveness of insertion and maintenance bundles to prevent central-line-associated bloodstream infections in critically ill patients of all ages: a systematic review and meta-analysis. Lancet Infect Dis 2016;16:724-34. 25. Chun JY, Seo HK, Kim MK, Shin MJ, Kim SY, Kim M, et al. Impact of a hand hygiene campaign in a tertiary hospital in South Korea on the rate of hospital-onset methicillin-resistant Staphylococcus aureus bacteremia and economic evaluation of the campaign. Am J Infect Control 2016;44:1486-91. 26. Kim YC, Kim MH, Song JE, Ahn JY, Oh DH, Kweon OM, et al. Trend of methicillinresistant Staphylococcus aureus (MRSA) bacteremia in an institution with a high rate of MRSA after the reinforcement of antibiotic stewardship and hand hygiene. Am J Infect Control 2013;41:e39-43.