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Objective: To establish the epidemiology of cardiac implantable electronic device (CIED) infections in Alberta, Canada, using validated administrative data. Design: Retrospective, population-based cohort study. Setting: Alberta Health Services is a province-wide health system that services all of Alberta, Canada. Participants: Adult patients who underwent first-time CIED implantation or generator replacement in Alberta, Canada, between January 1, 2011, and December 31, 2019. Methods: CIED implant patients were identified from the Paceart database. Patients who developed an infection within 1 year of the index procedure were identified through validated administrative data (International Classification of Diseases, Tenth Revision in Canada). Demographic characteristics of patients were summarized. Logistic regression models were used to analyze device type, comorbidities, and demographics associated with infection rates and mortality. Results: Among 27,830 CIED implants, there were 205 infections (0.74%). Having 2 or more comorbidities was associated with higher infection risk. Generator replacement procedures (odds ratio [OR], 0.55; 95% confidence interval [CI], 0.34–0.84; P = .008), age increase of every 10 years (OR, 0.73; 95% CI, 0.66–0.82; P ≤ .001), and index procedure after 2014 were associated with decreased risk. Comparing the infected to uninfected groups, the hospitalization rates were 2.63 compared to 0.69, and the mortality rates were 10.73% compared to 3.49%, respectively (P < .001). Conclusions: There is a slightly lower overall rate of CIED infections Alberta, Canada compared to previously described epidemiology. Implants after 2014, and generator replacements showed a decreased burden of infection. Patients with younger age, and 2 or more comorbidities are at greatest risk of CIED infection. The burden of hospitalization and mortality is substantially higher in infected patients.

Objective:To evaluate the cost of 1-stage and 2-stage revisions, debridement, antibiotic and implant retention (DAIR) and DAIR with liner exchange for complex surgical site infections (SSIs) following hip and knee replacements.Design:Retrospective population-based economic analysis of patients undergoing intervention for SSIs between April 1, 2012 and March 31, 2019.Setting:The study was conducted in the Calgary zone of Alberta Health Services (AHS) in Canada.Participants:Individuals >18 years with complex SSI following hip or knee replacement.Methods:Patients with complex SSIs were identified using the AHS infection prevention and control database. A combination of microcosting and gross costing methods were used to estimate 12- and 24-month costs following the initial hospital admission for arthroplasty. Subgroup, inverse Gaussian and γ regression analyses were used to evaluate the impact of age and comorbidities on cost.Results:In total, 142 patients with complex SSIs were identified, with a mean age of 66.8 years. Total direct medical costs in United States dollars of 2-stage revisions were ($100,992 (95% CI, 34,587–167,396) at 12 months. The 1-stage revision ($41,176; 95% CI, 23,361–58,991), DAIR with liner exchange ($41,267; 95% CI, 29,923–52,612) and DAIR ($46,605; 95% CI, 15,277–76,844) were associated with fewer costs at 12 months. Age >65 years and chronic complications of diabetes and hypertension were associated with increased costs in subgroup and regression analysis.Conclusions:Medical costs are highest at 12 months and for 2-stage revisions in hip and knee complex SSI cases. Further work should explore surgical outcomes correlated with costs to enhance patient care.

Objective Surgical site infections (SSIs) are a serious and costly post-op complication. Generating SSI rates often requires labor-intensive methods, but increasing numbers of publications reported SSI rates using administrative data. Methods Index laminectomy and spinal fusion procedures were identified using Canadian Classification of Health Interventions (CCI) procedure codes for inpatients and outpatients in the province of Alberta, Canada between 2008 and 2015. SSIs occurring in the year postsurgery were identified using the International Classification of Diseases, 10th Revision, Canada (ICD-10-CA) diagnosis and CCI procedure codes indicative of post-op infection. Rates of SSIs and case characteristics were reported. Results Over the 8-year study period, 21,222 index spinal procedures were identified of which 12,027 (56.7%) were laminectomy procedures, with 322 SSIs identified, an SSI rate of 2.7 per 100 procedures. Of the 9,195 (43.3%) fusion procedures, 298 were identified as an SSI, an SSI rate of 3.2 per 100 procedures. This study found SSI rates increased from 2008 and 2015, and rates were the highest in the 0-18 year age group. Conclusions The rates reported in this study were similar to published SSI rates using traditional surveillance methods, suggesting administrative data may be a viable method for reporting SSI rates following spinal procedures. Further work is needed to validate SSIs identified using administrative data by comparing to traditional surveillance.

Asymptomatic coronavirus disease 2019 (COVID-19) has been reported as a significant driver of COVID-19 outbreaks. Our hospital ward outbreak analysis suggests that comprehensive symptoms and signs assessment, in combination with adequate follow-up, allows a more precise determination of COVID-19 symptoms. Asymptomatic infection was quite uncommon among adults in this setting.

Background Clostridioides difficile infection (CDI) is one of the most common health care-associated infections. This study assessed the validity of the Discharge Abstract Database (DAD) compared to a traditional clinical surveillance method for identifying CDI. Methods Retrospective analysis of all DAD records with International Statistical Classification of Diseases and Related Health Problems 10th Revision (ie, ICD-10) diagnostic code A04.7 (enterocolitis due to CDI) between April 2015 and March 2019 were compared to a clinical dataset of positive inpatient CDI for all acute care facilities in Alberta, Canada. Sensitivity and positive predictive values were calculated using R version 3.6.0. Results The DAD had a sensitivity of 85.0% (95% confidence interval: 84.1%-85.8%) and a positive predictive value of 80.0% (95% confidence interval: 79.2%-80.0%). The CDI rate per 1,000 admissions over the study period was 28% higher in the DAD compared to Infection Prevention and Control surveillance. Discussion The DAD does not distinguish symptomatic cases from asymptomatic cases and so indicators to identify symptomatic disease would need to be applied, potentially through a linkage to antibiotic treatment orders available in patient management systems. Conclusions The DAD is moderately sensitive for identifying symptomatic CDI cases in Alberta, Canada and caution should be applied when interpreting rates based on administrative data.

Objective:Adverse outcomes following Clostridioides difficile infection (CDI) are not often reported for long-term care facility (LTCF) residents. We focused on the adverse outcomes due to CDI identified in Alberta LTCFs.Methods:All positive Clostridioides difficile stool specimens identified by laboratory-identified (LabID) event surveillance in Alberta from 2011 to 2018, along with Alberta Continuing Care Information System, were used to define CDI in Alberta LTCFs. CDI cases were classified as long-term care onset, hospital onset, and community onset. Laboratory records were linked to provincial databases to analyze acute-care admissions and mortality within 30-day post CDI. Age, sex, case classification, episode, and operator type, were investigated using logistic regression.Results:Overall, 902 CDI cases were identified in 762 LTCF residents. Of all CDI events, 860 (95.3%) were long-term care onset, 38 (4.2%) were hospital onset, and 4 (0.4%) were community onset. The CDI rate was 2.0 of 100,000 resident days. In total, 157 residents (20.6%) had 30-day all-cause mortality, 126 CDI cases (14.0%) had 30-day all-cause acute-care admissions. The 30-day all-cause mortality rate was significantly higher in residents aged >80 versus ≤80 years (24.9 vs 12.3 per 100 residents; P < .05). Residents aged >80 years, with hospital-onset CDI, and those staying in private or voluntary LTCFs were more likely to have 30-day all-cause acute-care admissions.Conclusions:The prevalence of CDI adverse outcomes is in LTCFs was found to be high using LabID event surveillance. Annual review of CDI adverse outcomes using LabID event can minimize the burden of surveillance and standardize the process across all Alberta LTCFs.

In a population-based, five-year retrospective cohort study of 5304 adult patients with hospital-acquired Clostridioides difficile infection across Alberta (N=101 hospitals), 30-day all-cause and attributable mortality were 12.2% and 4.5%, respectively. Patients >75 years of age had the highest odds of attributable mortality (odds ratio (OR) 9.34, 95% confidence interval (CI) 2.92-29.83) and largest difference in mean length of stay (11.7 days, 95% CI 8.2-15.2). A novel finding was that elevated white blood cell count at admission was associated with reduced attributable mortality (OR 0.67, 95% CI 0.50-0.90) which deserves further study. Advancing age was incrementally and significantly associated with all outcomes.

Objective:To determine the attributable cost and length of stay of hospital-acquired Clostridioides difficile infection (HA-CDI) from the healthcare payer perspective using linked clinical, administrative, and microcosting data.Design:A retrospective, population-based, propensity-score–matched cohort study.Setting:Acute-care facilities in Alberta, Canada.Patients:Admitted adult (≥18 years) patients with incident HA-CDI and without CDI between April 1, 2012, and March 31, 2016.Methods:Incident cases of HA-CDI were identified using a clinical surveillance definition. Cases were matched to noncases of CDI (those without a positive C. difficile test or without clinical CDI) on propensity score and exposure time. The outcomes were attributable costs and length of stay of the hospitalization where the CDI was identified. Costs were expressed in 2018 Canadian dollars.Results:Of the 2,916 HA-CDI cases at facilities with microcosting data available, 98.4% were matched to 13,024 noncases of CDI. The total adjusted cost among HA-CDI cases was 27% greater than noncases of CDI (ratio, 1.27; 95% confidence interval [CI], 1.21–1.33). The mean attributable cost was $18,386 (CAD 2018; USD $14,190; 95% CI, $14,312–$22,460; USD $11,046-$17,334). The adjusted length of stay among HA-CDI cases was 13% greater than for noncases of CDI (ratio, 1.13; 95% CI, 1.07–1.19), which corresponds to an extra 5.6 days (95% CI, 3.10–8.06) in length of hospital stay per HA-CDI case.Conclusions:In this population-based, propensity score matched analysis using microcosting data, HA-CDI was associated with substantial attributable cost.

SARS-CoV-2 has been detected in wastewater and its abundance correlated with community COVID-19 cases, hospitalizations and deaths. We sought to use wastewater-based detection of SARS-CoV-2 to assess the epidemiology of SARS-CoV-2 in hospitals. Between August and December 2020, twice-weekly wastewater samples from three tertiary-care hospitals (totaling >2100 dedicated inpatient beds) were collected. Hospital-1 and Hospital-2 could be captured with a single sampling point whereas Hospital-3 required three separate monitoring sites. Wastewater samples were concentrated and cleaned using the 4S-silica column method and assessed for SARS-CoV-2 gene-targets (N1, N2 and E) and controls using RT-qPCR. Wastewater SARS-CoV-2 as measured by quantification cycle (Cq), genome copies and genomes normalized to the fecal biomarker PMMoV were compared to the total daily number of patients hospitalized with active COVID-19, confirmed cases of hospital-acquired infection, and the occurrence of unit-specific outbreaks. Of 165 wastewater samples collected, 159 (96%) were assayable. The N1-gene from SARS-CoV-2 was detected in 64.1% of samples, N2 in 49.7% and E in 10%. N1 and N2 in wastewater increased over time both in terms of the amount of detectable virus and the proportion of samples that were positive, consistent with increasing hospitalizations at those sites with single monitoring points (Pearson's r=0.679, P, Graphical Abstract Image, graphical abstract

Background As a result of the novel coronavirus disease 2019 (COVID-19), there have been widespread changes in healthcare access. We conducted a retrospective population-based study in Alberta, Canada (population 4.4 million), where there have been approximately 1550 hospital admissions for COVID-19, to determine the impact of COVID-19 on hospital admissions and emergency department (ED visits), following initiation of a public health emergency act on March 15, 2020. Methods We used multivariable negative binomial regression models to compare daily numbers of medical/surgical hospital admissions via the ED between March 16-September 23, 2019 (pre COVID-19) and March 16-September 23, 2020 (post COVID-19 public health measures). We compared the most frequent diagnoses for hospital admissions pre/post COVID-19 public health measures. A similar analysis was completed for numbers of daily ED visits for any reason with a particular focus on ambulatory care sensitive conditions (ACSC). Findings There was a significant reduction in both daily medical (incident rate ratio (IRR) 0.86, p Conclusions Despite a relatively low volume of COVID-19 hospital admissions in Alberta, there was an extensive impact on our healthcare system with fewer admissions to hospital and ED visits. This work generates hypotheses around causes for reduced hospital admissions and ED visits which warrant further investigation. As most publicly funded health systems struggle with health-system capacity routinely, understanding how these reductions can be safely sustained will be critical.

BackgroundSARS-CoV-2 has been detected in wastewater and its abundance correlated with community COVID-19 cases, hospitalizations and deaths. We sought to use wastewater-based detection of SARS-CoV-2 to assess the epidemiology of SARS-CoV-2 in hospitals.MethodsBetween August and December 2020, twice-weekly wastewater samples from three tertiary-care hospitals (totaling >2100 dedicated inpatient beds) were collected. Wastewater samples were concentrated and cleaned using the 4S-silica column method and assessed for SARS-CoV-2 gene-targets (N1, N2 and E) and controls using RT-qPCR. Wastewater SARS-CoV-2 as measured by quantification cycle (Cq), genome copies and genomes normalized to the fecal biomarker PMMoV were compared to the total daily number of patients hospitalized with active COVID-19, confirmed cases of hospital-acquired infection, and the occurrence of unit-specific outbreaks.ResultsOf 165 wastewater samples collected, 159 (96%) were assayable. The N1-gene from SARS-CoV-2 was detected in 64.1% of samples, N2 in 49.7% and E in 10%. N1 and N2 in wastewater increased over time both in terms of amount of detectable virus and the proportion of samples that were positive, consistent with increasing hospitalizations (Pearson’s r=0.679, PConclusionsWastewater-based monitoring of SARS-CoV-2 represents a promising tool for SARS-CoV-2 passive surveillance and case identification, containment, and mitigation in acute-care medical facilities.Supplemental Material includedKey-points summarySAS-CoV-2 RNA is detectable in hospital wastewater. Wastewater SARS-CoV-2 RNA increases in conjunction with COVID-19-related hospitalizations. Spikes in SARS-CoV-2 wastewater signal correspond to incident hospital-acquired cases and outbreaks, suggesting passive surveillance via wastewater has great promise for COVID-19 monitoring.

Background:Clostridioides difficile infection (CDI) is the most common cause of infectious diarrhea in hospitalized patients. Probiotics have been studied as a measure to prevent CDI. Timely probiotic administration to at-risk patients receiving systemic antimicrobials presents significant challenges. We sought to determine optimal implementation methods to administer probiotics to all adult inpatients aged 55 years receiving a course of systemic antimicrobials across an entire health region. Methods: Using a randomized stepped-wedge design across 4 acute-care hospitals (n = 2,490 beds), the probiotic Bio-K+ was prescribed daily to patients receiving systemic antimicrobials and was continued for 5 days after antimicrobial discontinuation. Focus groups and interviews were conducted to identify barriers, and the implementation strategy was adapted to address the key identified barriers. The implementation strategy included clinical decision support involving a linked flag on antibiotic ordering and a 1-click order entry within the electronic medical record (EMR), provider and patient education (written/videos/in-person), and local site champions. Protocol adherence was measured by tracking the number of patients on therapeutic antimicrobials that received BioK+ based on the bedside nursing EMR medication administration records. Adherence rates were sorted by hospital and unit in 48- and 72-hour intervals with recording of percentile distribution of time (days) to receipt of the first antimicrobial. Results: In total, 340 education sessions with >1,800 key stakeholders occurred before and during implementation across the 4 involved hospitals. The overall adherence of probiotic ordering for wards with antimicrobial orders was 78% and 80% at 48 and 72 hours, respectively over 72 patient months. Individual hospital adherence rates varied between 77% and 80% at 48 hours and between 79% and 83% at 72 hours. Of 246,144 scheduled probiotic orders, 94% were administered at the bedside within a median of 0.61 days (75th percentile, 0.88), 0.47 days (75th percentile, 0.86), 0.71 days (75th percentile, 0.92) and 0.67 days (75th percentile, 0.93), respectively, at the 4 sites after receipt of first antimicrobial. The key themes from the focus groups emphasized the usefulness of the linked flag alert for probiotics on antibiotic ordering, the ease of the EMR 1-click order entry, and the importance of the education sessions. Conclusions: Electronic clinical decision support, education, and local champion support achieved a high implementation rate consistent across all sites. Use of a 1-click order entry in the EMR was considered a key component of the success of the implementation and should be considered for any implementation strategy for a stewardship initiative. Achieving high prescribing adherence allows more precision in evaluating the effectiveness of the probiotic strategy.Funding: Partnerships for Research and Innovation in the Health System, Alberta Innovates/Health Solutions Funding: AwardDisclosures: None

Background: Hospital-acquired Clostridioides difficile infection (HA-CDI) rates are highly variable over time, posing problems for research assessing interventions that might improve rates. By understanding seasonality in HA-CDI rates and the impacts that other factors such as influenza admissions might have on these rates, we can account for them when establishing the relationship between interventions and infection rates. We assessed whether there were seasonal trends in HA-CDI and whether they could be accounted for by influenza rates. Methods: We assessed HA-CDI rates per 10,000 patient days, and the rate of hospitalized patients with influenza per 1,000 admissions in 4 acute-care facilities (n = 2,490 beds) in Calgary, Alberta, from January 2016 to December 2018. We used 4 statistical approaches in R (version 3.5.1 software): (1) autoregressive integrated moving average (ARIMA) to assess dependencies and trends in each of the monthly HA-CDI and influenza series; (2) cross correlation to assess dependencies between the HA-CDI and influenza series lagged over time; (3) Poisson harmonic regression models (with sine and cosine components) to assess the seasonality of the rates; and (4) Poisson regression to determine whether influenza rates accounted for seasonality in the HA-CDI rates. Results: Conventional ARIMA approaches did not detect seasonality in the HA-CDI rates, but we found strong seasonality in the influenza rates. A cross-correlation analysis revealed evidence of correlation between the series at a lag of zero (R = 0.41; 95% CI, 0.10–0.65) and provided an indication of a seasonal relationship between the series (Fig. 1). Poisson regression suggested that influenza rates predicted CDI rates (P < .01). Using harmonic regression, there was evidence of seasonality in HA-CDI rates (2 [2 df] = 6.62; P < .05) and influenza rates (2 [2 df] = 1,796.6; P < .001). In a Poisson model of HA-CDI rates with both the harmonic components and influenza admission rates, the harmonic components were no longer predictive of HA-CDI rates. Conclusions: Harmonic regression provided a sensitive means of identifying seasonality in HA-CDI rates, but the seasonality effect was accounted for by influenza admission rates. The relationship between HA-CDI and influenza rates is likely mediated by antibiotic prescriptions, which needs to be assessed. To improve precision and reduce bias, research on interventions to reduce HA-CDI rates should assess historic seasonality in HA-CDI rates and should account for influenza admissions.Funding: NoneDisclosures: None

Background Clostridioides difficile infection (CDI) is one of the most common health care–associated infections. This study assessed the validity of a laboratory-based surveillance method as compared with a traditional, clinical surveillance method to identify hospital-acquired CDIs. Methods Retrospective analysis of positive C difficile laboratory records between April 2015 and March 2017 were compared with a clinical dataset of positive inpatient C difficile cases for all acute care facilities in Alberta, Canada. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated using STATA/IC 13.0. Results The laboratory surveillance method had a sensitivity of 96.6% (95% confidence interval [CI], 95.7%-97.3%) and a specificity of 65.7% (95% CI, 63.6%-67.8%); positive predictive value and negative predictive value were 74.3% (95% CI, 73.2%-75.5%) and 94.9% (95% CI, 93.7%-95.9%), respectively. Discussion To date, the breadth of research on alternate CDI surveillance systems has focused on the use of International Statistical Classification of Diseases and Related Health Problems 9th and 10th Revision coding mechanisms. Our results expand on the published literature, as a laboratory approach may provide more timely information, with a smaller amount of misclassified cases. Conclusions Using a laboratory surveillance method to capture hospital-acquired CDI cases is highly sensitive but not overly specific. Changes to improve the specificity of this method are provided.

SUMMARYPatients with methicillin-resistant Staphylococcus aureus (MRSA) clones, which were traditionally seen in the community setting (USA400/CMRSA7 and USA300/CMRSA10), are often identified as hospital-acquired (HA) infections using Infection Prevention and Control (IPC) surveillance definitions. This study examined the demographics and healthcare risk factors of patients with HA-MRSA to help understand if community MRSA clones are from a source internal or external to the hospital setting. Despite USA300/CMRSA10 being the predominant clone in Alberta, hospital clones (USA100/CMRSA2) still dominated in the acute care setting. In the Alberta hospitalized population, patients with USA400/CMRSA7 and USA300/CMRSA10 clones were significantly younger, had fewer comorbidities, and a greater proportion had none or ambulatory care-only healthcare exposure. These findings suggest that there are two distinct populations of HA-MRSA patients, and the patients with USA400/CMRSA7 and USA300/CMRSA10 clones identified in hospital more greatly resemble patients affected by those clones in the community. It is possible that epidemiological assessment overidentifies HA acquisition of MRSA in patients unscreened for MRSA on admission to acute care.

Background: Infection Prevention and Control (IPC) for Alberta Health Services and Covenant Health in the province of Alberta, Canada conducts surveillance for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococcus (VRE) on all individuals admitted to acute-care and acute tertiary-care rehabilitation care facilities. Objective: The objective of this study was to determine the consistency and accuracy of infection decisions for MRSA and VRE. Methods: Surveillance cases of antibiotic-resistant organisms (AROs) collected using the provincial data entry surveillance platform between April 1, 2015, and March 31, 2017, across the province were reabstracted by infection control professionals and physicians using the NHSN infection definitions and compared to the original case severity decisions. Interrater agreement (Cohen’s ) and validity (sensitivity, specificity and predictive values) were calculated to compare the original and reabstracted infection decisions. Results: Collectively, 97% (87 of 90) of the IPC program staff and physicians who were initially invited re-abstracted 264 MRSA cases and 103 VRE cases within the review period. Provincially, 20% of the ARO cases reviewed (74 of 367) differed from the original infection decision. Among these 74 cases, 46 cases (34 MRSA and 12 VRE cases) changed from infection (original decision) to colonization (reabstracted decision) and 28 cases (21 MRSA and 7 VRE cases) changed from colonization to infection. The Cohen values for MRSA and VRE were 0.55 and 0.56, respectively, suggesting a moderate level of agreement for decisions made among IPC program staff. The sensitivity of the infection decision was higher with MRSA (86.5%) than for VRE (74.1%), meaning that there were more MRSA cases than VRE cases classified as infection in the original decision that remained infection following the review. Conclusions: Observed discordances on infection decisions were identified and may be attributed (1) to variations in the interpretation of the NHSN definitions, (2) to additional information that may have been available in the re-abstracted review compared to the original review, or (3) a difference in the information that was accessed to perform the original review compared to the reabstraction. This data-quality review provided an opportunity for IPC staff and physicians to become more familiar with infection definitions and such reviews will continue to be a regular process used to assess data quality within the IPC department.Funding: NoneDisclosures: None

Background.Electronic surveillance systems (ESSs) that utilize existing information in databases are more efficient than conventional infection surveillance methods.Objective.To develop an ESS for monitoring bloodstream infections (BSIs) and assess whether data obtained from the ESS were in agreement with data obtained by traditional manual medical-record review.Methods.An ESS was developed by linking data from regional laboratory and hospital administrative databases. Definitions for excluding BSI episodes representing contamination and duplicate episodes were developed and applied. Infections were classified as nosocomial infections, healthcare-associated community-onset infections, or community-acquired infections. For a random sample of episodes, data in the ESS were compared with data obtained by independent medical chart review.Results.From the records of the 306 patients whose infections were selected for comparative review, the ESS identified 323 episodes of BSI, of which 107 (33%) were classified as healthcare-associated community-onset infections, 108 (33%) were classified as community-acquired infections, 107 (33%) were classified as nosocomial infections, and 1 (0.3%) could not be classified. In comparison, 310 episodes were identified by use of medical chart review, of which 116 (37%) were classified as healthcare-associated community-onset infections, 95 (31%) as community-acquired infections, and 99 (32%) as nosocomial infections. For 302 episodes of BSI, there was concordance between the findings of the ESS and those of traditional manual chart review. Of the additional 21 discordant episodes that were identified by use of the ESS, 17 (81%) were classified as representing isolation of skin contaminants, by use of chart review. Of the additional 8 discordant episodes further identified by use of chart review, most were classified as repeat or polymicrobial episodes of disease. There was an overall 85% agreement between the findings of the ESS and those of chart review (K = 0.78; standard error, K = 0.04) for classification according to location of acquisition.Conclusion.Our novel ESS allows episodes of BSI to be identified and classified with a high degree of accuracy. This system requires validation in other cohorts and settings.