Improved hospital-level risk adjustment for surveillance of healthcare-associated bloodstream infections: a retrospective cohort study

Use of a Victorian statewide surveillance program to evaluate the burden of healthcare-associated Staphylococcus aureus bacteraemia and Clostridioides difficile infection in patients with cancer

BACKGROUND

Patients with cancer are at high risk for infection, but the epidemiology of healthcare-associated Staphylococcus aureus bacteraemia (HA-SAB) and Clostridioides difficile infection (HA-CDI) in Australian cancer patients has not previously been reported.

AIMS

To compare the cumulative aggregate incidence and time trends of HA-SAB and HA-CDI in a predefined cancer cohort with a mixed statewide patient population in Victoria, Australia.

METHODS

All SAB and CDI events in patients admitted to Victorian healthcare facilities between 1^st July 2010 and 31^st December 2018 were submitted to the Victorian Healthcare Associated Infection Surveillance System Coordinating Centre. Descriptive analyses and multilevel mixed-effects Poisson regression modelling were applied to a standardised data extract.

RESULTS

In total, 10,608 and 13,118 SAB and CDI events were reported across 139 Victorian healthcare facilities, respectively. Of these, 89 (85%) and 279 (88%) were healthcare-associated in the cancer cohort compared to 34% (3,561/10,503) and 66% (8,403/12,802) in the statewide cohort. The aggregate incidence was more than two-fold higher in the cancer compared to the statewide cohort for HA-SAB (2.25 [95% CI: 1.74-2.77] vs. 1.11 [95% CI: 1.07-1.15] HA-SABs/10,000 OBDs) and three-fold higher for HA-CDI (6.26 [95% CI: 5.12-7.41] vs. 2.31 [95% CI: 2.21-2.42] HA-CDIs/10,000 OBDs). Higher quarterly diminishing rates were observed in the cancer cohort than the statewide data for both infections.

CONCLUSIONS

Our findings demonstrate a higher burden of HA-SAB and HA-CDI in a cancer cohort when compared with state data and highlight the need for cancer-specific targets and benchmarks to meaningfully support quality improvement. This article is protected by copyright. All rights reserved.

A ten-year review of healthcare-associated bloodstream infections from forty hospitals in Québec, Canada

OBJECTIVE

Healthcare-associated bloodstream infections (HABSI) are a significant cause of morbidity and mortality worldwide. In Québec, Canada, HABSI arising from acute-care hospitals have been monitored since April 2007 through the Surveillance des bactériémies nosocomiales panhospitalières (BACTOT) program, but this is the first detailed description of HABSI epidemiology.

METHODS

This retrospective, descriptive study was conducted using BACTOT surveillance data from hospitals that participated continuously between April 1, 2007, and March 31, 2017. HABSI cases and rates were stratified by hospital type and/or infection source. Temporal trends of rates were analyzed by fitting generalized estimating equation Poisson models, and they were stratified by infection source.

RESULTS

For 40 hospitals, 13,024 HABSI cases and 23,313,959 patient days were recorded, for an overall rate of 5.59 per 10,000 patient days (95% CI, 5.54-5.63). The most common infection sources were catheter-associated BSIs (23.0%), BSIs secondary to a urinary focus (21.5%), and non-catheter-associated primary BSIs (18.1%). Teaching hospitals and nonteaching hospitals with ICUs often had rates higher than nonteaching hospitals without ICUs. Annual HABSI rates did not exhibit statistically significant changes from year to year. Non-catheter-associated primary BSIs were the only HABSI type that exhibited a sustained change across the 10 years, increasing from 0.69 per 10,000 patient days (95% CI, 0.59-0.80) in 2007-2008 to 1.42 per 10,000 patient days (95% CI, 1.27-1.58) in 2016-2017.

CONCLUSIONS

Despite ongoing surveillance, overall HABSI rates have not decreased. The effect of BACTOT participation should be more closely investigated, and targeted interventions along alternative surveillance modalities should be considered, prioritizing high-burden and potentially preventable BSI types.

Characterising health care-associated bloodstream infections in public hospitals in Queensland, 2008-2012

OBJECTIVE

To describe the epidemiology and rates of all health care-associated bloodstream infections (HA-BSIs) and of specific HA-BSI subsets in public hospitals in Queensland.

DESIGN AND SETTING

Standardised HA-BSI surveillance data were collected in 23 Queensland public hospitals, 2008-2012.

MAIN OUTCOME MEASURES

HA-BSIs were prospectively classified in terms of place of acquisition (inpatient, non-inpatient); focus of infection (intravascular catheter-associated, organ site focus, neutropenic sepsis, or unknown focus); and causative organisms. Inpatient HA-BSI rates (per 10,000 patient-days) were calculated.

RESULTS

There were 8092 HA-BSIs and 9418 causative organisms reported. Inpatient HA-BSIs accounted for 79% of all cases. The focus of infection in 2792 cases (35%) was an organ site, intravascular catheters in 2755 (34%; including 2240 central line catheters), neutropenic sepsis in 1063 (13%), and unknown in 1482 (18%). Five per cent (117 of 2240) of central line-associated BSIs (CLABSIs) were attributable to intensive care units (ICUs). Eight groups of organisms provided 79% of causative agents: coagulase-negative staphylococci (18%), Staphylococcus aureus (15%), Escherichia coli (11%), Pseudomonas species (9%), Klebsiella pneumoniae/oxytoca (8%), Enterococcus species (7%), Enterobacter species (6%), and Candida species (5%). The overall inpatient HA-BSI rate was 6.0 per 10,000 patient-days. The rates for important BSI subsets included: intravascular catheter-associated BSIs, 1.9 per 10,000 patient-days; S. aureus BSIs, 1.0 per 10,000 patient-days; and methicillin-resistant S. aureus BSIs, 0.3 per 10,000 patient-days.

CONCLUSIONS

The rate of HA-BSIs in Queensland public hospitals is lower than reported by similar studies elsewhere. About one-third of HA-BSIs are attributable to intravascular catheters, predominantly central venous lines, but the vast majority of CLABSIs are contracted outside ICUs. Different sources of HA-BSIs require different prevention strategies.

Evaluating the Use of the Case Mix Index for Risk Adjustment of Healthcare-Associated Infection Data: An Illustration using Clostridium difficile Infection Data from the National Healthcare Safety Network

BACKGROUND Case mix index (CMI) has been used as a facility-level indicator of patient disease severity. We sought to evaluate the potential for CMI to be used for risk adjustment of National Healthcare Safety Network (NHSN) healthcare-associated infection (HAI) data. METHODS NHSN facility-wide laboratory-identified Clostridium difficile infection event data from 2012 were merged with the fiscal year 2012 Inpatient Prospective Payment System (IPPS) Impact file by CMS certification number (CCN) to obtain a CMI value for hospitals reporting to NHSN. Negative binomial regression was used to evaluate whether CMI was significantly associated with healthcare facility-onset (HO) CDI in univariate and multivariate analysis. RESULTS Among 1,468 acute care hospitals reporting CDI data to NHSN in 2012, 1,429 matched by CCN to a CMI value in the Impact file. CMI (median, 1.49; interquartile range, 1.36-1.66) was a significant predictor of HO CDI in univariate analysis (P<.0001). After controlling for community onset CDI prevalence rate, medical school affiliation, hospital size, and CDI test type use, CMI remained highly significant (P<.0001), with an increase of 0.1 point in CMI associated with a 3.4% increase in the HO CDI incidence rate. CONCLUSIONS CMI was a significant predictor of NHSN HO CDI incidence. Additional work to explore the feasibility of using CMI for risk adjustment of NHSN data is necessary. Infect. Control Hosp. Epidemiol. 2015;37(1):19-25.

A case-control study to identify risk factors for totally implantable central venous port-related bloodstream infection

PURPOSE

To date, the risk factors for central venous port-related bloodstream infection (CVPBSI) in solid cancer patients have not been fully elucidated. We conducted this study in order to determine the risk factors for CVP-BSI in patients with solid cancer.

MATERIALS AND METHODS

A total of 1,642 patients with solid cancer received an implantable central venous port for delivery of chemotherapy between October 2008 and December 2011 in a single center. CVP-BSI was diagnosed in 66 patients (4%). We selected a control group of 130 patients, who were individually matched with respect to age, sex, and catheter insertion time.

RESULTS

CVP-BSI occurred most frequently between September and November (37.9%). The most common pathogen was gram-positive cocci (n=35, 53.0%), followed by fungus (n=14, 21.2%). Multivariate analysis identified monthly catheter-stay as a risk factor for CVP-BSI (p=0.000), however, its risk was lower in primary gastrointestinal cancer than in other cancer (p=0.002). Initial metastatic disease and long catheter-stay were statistically significant factors affecting catheter life span (p=0.005 and p=0.000). Results of multivariate analysis showed that recent transfusion was a risk factor for mortality in patients with CVP-BSI (p=0.047).

CONCLUSION

In analysis of the results with respect to risk factors, prolonged catheter-stay should be avoided as much as possible. It is necessary to be cautious of CVP-BSI in metastatic solid cancer, especially non-gastrointestinal cancer. In addition, avoidance of unnecessary transfusion is essential in order to reduce the mortality of CVP-BSI. Finally, considering the fact that confounding factors may have affected the results, conduct of a well-designed prospective controlled study is warranted.

Development of a risk-adjustment model for antimicrobial utilization data in 21 public hospitals in Queensland, Australia (2006-11)

OBJECTIVES

Making valid comparisons of antimicrobial utilization between hospitals requires risk adjustment for each hospital's case mix. Data on individual patients may be unavailable or difficult to process. Therefore, risk adjustment for antimicrobial usage frequently needs to be based on a hospital's services. This study evaluated such a strategy for hospital antimicrobial utilization.

METHODS

Data were obtained on five broad subclasses of antibiotics [carbapenems, β-lactam/β-lactamase inhibitor combinations (BLBLIs), fluoroquinolones, glycopeptides and third-generation cephalosporins] from the Queensland pharmacy database (MedTrx) for 21 acute public hospitals (2006-11). Eleven clinical services and a variable for hospitals from the tropical region were employed for risk adjustment. Multivariable regression models were used to identify risk and protective services for these antibiotics. Funnel plots were used to display hospitals' antimicrobial utilization.

RESULTS

Total inpatient antibiotic utilization for these antibiotics increased from 130.6 defined daily doses (DDDs)/1000 patient-days in 2006 to 155.8 DDDs/1000 patient-days in 2011 (P < 0.0001). Except for third-generation cephalosporins, the average utilization rate was higher for intensive care, renal/nephrology, cardiac, burns/plastic surgery, neurosurgery, transplant and acute spinal services than for the respective reference group (no service). In addition, oncology, high-activity infectious disease and coronary care services were associated with higher utilization of carbapenems, BLBLIs and glycopeptides.

CONCLUSIONS

Our model predicted antimicrobial utilization rates by hospital services. The funnel plots displayed hospital utilization data after adjustment for variation among the hospitals. However, the methodology needs to be validated in other populations, ideally using a larger group of hospitals.

Mortality and hospital stay associated with resistant Staphylococcus aureus and Escherichia coli bacteremia: estimating the burden of antibiotic resistance in Europe

BACKGROUND

The relative importance of human diseases is conventionally assessed by cause-specific mortality, morbidity, and economic impact. Current estimates for infections caused by antibiotic-resistant bacteria are not sufficiently supported by quantitative empirical data. This study determined the excess number of deaths, bed-days, and hospital costs associated with blood stream infections (BSIs) caused by methicillin-resistant Staphylococcus aureus (MRSA) and third-generation cephalosporin-resistant Escherichia coli (G3CREC) in 31 countries that participated in the European Antimicrobial Resistance Surveillance System (EARSS).

METHODS AND FINDINGS

The number of BSIs caused by MRSA and G3CREC was extrapolated from EARSS prevalence data and national health care statistics. Prospective cohort studies, carried out in hospitals participating in EARSS in 2007, provided the parameters for estimating the excess 30-d mortality and hospital stay associated with BSIs caused by either MRSA or G3CREC. Hospital expenditure was derived from a publicly available cost model. Trends established by EARSS were used to determine the trajectories for MRSA and G3CREC prevalence until 2015. In 2007, 27,711 episodes of MRSA BSIs were associated with 5,503 excess deaths and 255,683 excess hospital days in the participating countries, whereas 15,183 episodes of G3CREC BSIs were associated with 2,712 excess deaths and 120,065 extra hospital days. The total costs attributable to excess hospital stays for MRSA and G3CREC BSIs were 44.0 and 18.1 million Euros (63.1 and 29.7 million international dollars), respectively. Based on prevailing trends, the number of BSIs caused by G3CREC is likely to rapidly increase, outnumbering the number of MRSA BSIs in the near future.

CONCLUSIONS

Excess mortality associated with BSIs caused by MRSA and G3CREC is significant, and the prolongation of hospital stay imposes a considerable burden on health care systems. A foreseeable shift in the burden of antibiotic resistance from Gram-positive to Gram-negative infections will exacerbate this situation and is reason for concern.

Funnel plots and risk-adjusted count data adverse events. A limitation of indirect standardisation

Reporting of hospital adverse event data is becoming increasingly mandated and this has motivated work on methods for the analysis and display of these data for groups of institutions. Currently, the method preferred by many workers is the funnel plot. Often, indirect standardisation is employed to produce these plots. It appears that, when used to display binary data such as surgical site infection or mortality data, the method is satisfactory. Increasingly, these data are risk-adjusted. However, risk adjustment of these data usually involves individual patients undergoing the same or similar procedures and the method does not appear to mislead. However, when dealing with count data such as bacteraemias it appears that this method can mislead, particularly where methods for risk adjustment of these data are used. Information about the hospitals or units of interest rather than individual patients is employed. For example, one hospital may have plastic and cardiac surgery units in which bacteraemias occur infrequently whereas another may provide treatment for renal failure (including transplantation) and have a large haematology-oncology unit (also including transplantation), each of which would expect higher bacteraemia rates. Moreover, the hospitals and units within them may differ substantially in size. It is well known that indirect standardisation can give biased results when denominators differ substantially. We illustrate this difficulty with risk-adjusted bacteraemia data from the Queensland Health Centre for Healthcare Infection, Surveillance and Prevention (CHRISP) database.

Sequential analysis of uncommon adverse outcomes

Sequential analysis of uncommon adverse outcomes (AEs) such as surgical site infections (SSIs) is desirable. Short postoperative lengths of stay (LOS) result in many SSIs occurring after discharge and they are often superficial. Deep and organ space (complex) SSIs occur less frequently but are detected more reliably and are suitable for monitoring wound care. Those occurring post-discharge usually require readmissison and can be counted accurately. Sequential analysis of meticillin-resistant Staphylococcus aureus bacteraemia is also needed. The key to prevention is to implement systems based on evidence, e.g. using 'bundles' and checklists. Regular mortality and morbidity audit meetings are required and these may need to be followed by independent audits. Sequential statistical analysis is desirable for data presentation, to detect changes, and to discourage tampering with processes when occasional AEs occur in a reliable system. Tabulations and cumulative observed minus expected (O-E) charts and funnel plots are valuable, supplemented in the presence of apparent 'runs' of AEs by cumulative sum analysis. Used prospectively, they may enable staff to visualise and detect patterns or shifts in rates and counts that might not otherwise be apparent.