Infection Control & Hospital Epidemiology
admissions per year, and a new online data entry platform was implemented to streamline data collection (Nosokos, Nosotech, Québec, Canada). The following information was collected for all participating facilities: health region, teaching status, number of beds and ICU beds, and proportion of patients ≥65 years of age. Facilities submitted overall and ICU-specific inpatient-days denominators for every administrative 4-week period. SPIN also gathered prespecified relevant variables for each HABSI case identified: patient demographics, date of diagnosis, unit in which the case arose, type of infection, microorganisms involved with antibiotic susceptibility profile, recent invasive procedures, risk factors for infection, suspected origin of acquisition, and com- plications resulting from the infection.
Case definitions
Episodes of BSI were identified using the National Healthcare Safety Network (NHSN) criteria.12 Cases had to meet at least 1 of the following criteria: (1) a patient with a recognized pathogen cultured from1 or more blood cultures not related to an infection at another site (primary BSI); or (2) a patient with a recognized pathogen cultured from 1 or more blood cultures related to an infection at another site (secondary BSI); or (3) a patient found to have a common skin contaminant cultured from 2 or more blood cultures <1 day apart with ≥1 of the following signs or symptoms: fever >38°C, chills, hypotension or hypothermia <37°C, apnea, or bradycardia (also primary BSI). Prior to April 1, 2010, a primary catheter-related BSI with a common skin contaminant only required 1 positive blood culture as long as the treating physician had initi- ated treatment. The data used for this analysis were corrected ret- rospectively to reject BSIs with <1 blood culture. BSIs were deemed healthcare-associated (HABSI) if they occurred >2 calendar days after admission, unless they resulted from a preceding admission or procedure.12 Primary BSIs were subtyped asBSIsassociated with a venous catheter (CA-BSI), either central or peripheral or non– catheter-associated primary BSIs (NCA-BSI). Secondary BSIs were subtyped as secondary to surgical site infections (BSI-SSIs), urinary tract infections (BSI-UTIs), pulmonary infections (BSI-PULMs), intra-abdominal infections (BSI-ABDOs), skin-and-soft-tissues infections (BSI-SSTs), bone-and-joint infections (BSI-BONEs) or any other primary focus (BSI-other). Between April 1, 2011, and March 31, 2013, primary BSIs following invasive procedures (clas- sified under NCA-BSI) were defined as cases occurring within 2 calendar days following the procedure. After 2013, the window of causality was returned to 7 calendar days. Dialysis-associated pri- mary BSIs arealsofollowedbyBACTOT but were not analyzedin this study because they predominantly occur in ambulatory setting.
Study design and analysis
This retrospective, descriptive study was conducted using BAC- TOT surveillance data from a closed cohort of eligible hospitals participating for at least 11 of 13 administrative periods annually from April 1, 2007, to March 31, 2017. Data pooled by hospital and administrative period were obtained directly from SPIN. Ethics approval was obtained from the McGill University Insti- tutional Review Board.
Numerators All incident HABSI cases among admitted patients were pooled by hospital and year and were stratified by type of infection and/
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or hospital type: nonteaching without an ICU, nonteaching with an ICU, or teaching.
Denominators Patient days were pooled by hospital and year and were stratified by hospital type. Every day spent at a participating hospital by a patient was counted as 1 patient day. Days of admission and discharge were each counted as half a day.
Descriptive analyses The characteristics of hospitals that met the inclusion criteria were described. A logistic regression was fitted to investigate any difference in the characteristics between included and excluded hospitals. The frequency distribution of HABSI subtypes over the 10-year period was reported. Annual and 10-year IRs were cal- culated by dividing the number of incident cases from each period by the total number of patient days of the same period and reported per 10,000 patient days. We calculated 95% confidence intervals (CIs) for these rates using the normal approximation method, which was further transformed to account for over- dispersion using the following formula:
exp 1:96 ffiffiffiffiffiffiffiffiffifficasesp IR ðÞ ; IR ´ exp 1:96 ffiffiffiffiffiffiffiffiffifficasesp
Generalized estimating equations (GEE) GEE Poisson regression models with exchangeable correlation structures were fitted for all HABSIs and each subtype. The variables in each model were administrative year, coded as a categorical variable with 10 levels (year 1 as reference), and hospital type, coded as a categorical variable with 3 levels: non- teaching hospital without an ICU as the reference, nonteaching hospital with an ICU, and teaching hospital. The incidence rate ratios (IRRs) are reported. All analyses were conducted using R version 3.4.1 with RStudio version 1.0.143 (RStudio Team, Boston, MA).
Results Cohort description
Of the 90 acute-care hospitals eligible to participate in BACTOT, 40 (44%) met the inclusion criteria. Between April 1, 2007, and March 31, 2017, a total of 13,024 HABSI cases were reported for 23,313,959 patient days (Table 1). The included hospitals con- tributed 47% of all BACTOT-recorded patient days in study year 10 (Y10, 2016–2017).13 Of the included hospitals, 36 participated in all 130 administrative periods, while the remaining 4 con- tributed 129 periods each. Also, 30% of the cohort (n=12) were teaching hospitals, all of which had ICUs. Nonteaching hospitals with ICUs formed 48% (n=19) of the cohort, while nonteaching hospitals without ICUs represented 23% (n=9). Hospital sizes varied between 29 and 549 beds (median, 188.5 beds), with a total of 8,488 beds. In hospitals with ICUs, the number of ICU beds ranged from 3 to 75 (median, 10 beds). Only 1 hospital was exclusively pediatric. Between 30% and 57% of a given hospital’s patient population was aged ≥65 years (median, 47%). No sta- tistically significant difference was detected between the included and excluded hospitals in the aforementioned characteristics.
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