Background: In Alberta, Canada, surgical site infections (SSIs) following total hip (THR) and knee replacements (TKR) are reported using 2 data sources: infection prevention and control (IPC), which surveys all THR and TKR using NHSN definitions and the Canadian International Classification of Disease, Tenth Revision (ICD-10-CA) codes, and the National Surgical Quality Improvement Program (NSQIP), which uses a systematic sampling process that involves an 8-day cycle schedule, modified NHSN definitions and current procedural terminology (CPT) codes. We compared the similarities and discrepancies in THR/TKR SSI reporting. Methods: A retrospective multisite cohort study of IPC and NSQIP THR/TKR SSI data at 4 hospitals was performed. SSI data were collected between September 1, 2015, and March 31, 2018. Demographic information and complex and total SSIs reported by IPC and NSQIP were compared for both THR and TKR surgeries. To determine whether both data sources reported similar trends over time, total SSIs by quarter were compared. Univariate analyses using a t test for age and the χ2 test for gender for complex SSIs and total SSIs was performed. The Pearson correlation and the Shapiro-Wilk test were used to assess the THR and TKR trends between the 2 data sources. A P value of <.05 was considered significant. Results: Following the removal of duplicates and missing data, 7,549 IPC and 2,037 NSQIP patients, respectively, were compared. Age, gender, and other demographic parameters were not significantly different. Total THR and TKR SSIs per 100 procedures using NSQIP data were significantly higher than the same rates using IPC data: THR, 2.25 versus 0.92 (P < .05) and TKR, 3.43 versus 1.26 (P < .05). Both IPC and NSQIP data indicated increasing total THR SSI rates over time, but with different magnitudes (r = 0.658). For total TKR SSI, the IPC rate decreased, whereas the NSQIP rate increased over the same period (r = 0.374). When superficial SSIs were excluded, the rates reported between IPC and NSQIP data by hospital and by procedure type were more comparable, with trends toward higher rates reported by NSQIP for THR than for TKR: THR, 1.19 versus 0.68 (P = 0.15) and TKR, 0.92 versus 0.80 (P = .68). Conclusions: Different approaches used to monitor SSIs following surgeries may lead to different results and trend patterns. NSQIP reports total SSI rates that are significantly higher than the IPC Alberta orthopedic population predominantly as a result of increased identification of superficial SSIs. Because the diagnosis of superficial SSIs may be less reliable, SSI reporting should focus on complex infections.

Funding: None

Disclosures: 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: None

Disclosures: None

Background: This review describes the epidemiology of carbapenemase-producing organisms (CPO) in both the community and hospitalized populations in the province of Alberta. Methods: Newly identified CPO-positive individuals from April 1, 2013, to March 31, 2018, were retrospectively reviewed from 3 data sources, which shared a common provincial CPO case definition: (1) positive CPO results from the Provincial Laboratory for Public Health, which provides all referral and confirmatory CPO testing, (2) CPO cases reported to Alberta Health, and (3) CPO surveillance from Alberta Health Services Infection Prevention and Control (IPC). The 3 data sources were collated, and initial CPO cases were classified according to their likely location of acquisition: hospital-acquired, hospital-identified, on admission, and community-identified. Risk factors and adverse outcomes were obtained from linkage to administrative data. Results: In total, 171 unique individuals were newly identified with a first-time CPO case. Also, 15% (25 of 171) were hospital-acquired (HA), 21% (36 of 171) were hospital-identified (HI), 33% (57 of 171) were on admission, and 31% (53 of 171) were community identified. Overall, 9% (5 of 171) resided in long-term care facilities. Of all patients in acute-care facilities, 30% (35 of 118) had infections and 70% were colonized. Overall, 38% (65 of 171) had an acute-care admission in the 1 year prior to CPO identification; 59% (63 of 106) of those who did not have a previous admission had received healthcare outside Alberta. A large proportion of on-admission cases (81%, 46 of 57) and community-identified (66%, 33 of 53) cases did not have any acute-care admissions in Alberta in the previous year. Overall, 10% (14 of 171) had ICU admissions in Alberta within 30 days of CPO identification, and 5% (8 of 171) died within 30 days. The most common carbapenemase gene identified was NDM-1 (53%, 90 of 171). Conclusions: These findings highlight the robust nature of Alberta’s provincial CPO surveillance network. We reviewed 3 different databases (laboratory, health ministry, IPC) to obtain comprehensive data to better understand the epidemiology of CPO in both the community and hospital settings. More than half of the individuals with CPO were initially identified in the community or on admission. Most had received healthcare outside Alberta, and no acute-care admissions occurred in Alberta in the previous year. It is important to be aware of the growing reservoir of CPO outside the hospital setting because it could impact future screening and management practices.

Funding: None

Disclosures: None

Background: Bloodstream infections (BSIs) are an important cause of morbidity and mortality in severely ill patients, contributing to increased length of stay and a higher cost of care. Surveillance of hospital-acquired (HA) BSI is considered a measure of quality of care and has been performed provincially in Alberta since 2011. Prior to October 2015, a nonstandardized, risk-factor–based VRE screening process was used. Screening practices for antibiotic-resistant organisms (AROs) were aligned in October 2015 with a provincially standardized admission screening tool to allow for early initiation of contact precautions for patients colonized or infected with MRSA or VRE. In this data review, we sought to determine whether this admission screening change influenced ARO infections through review of HA-BSI rates. Methods: Prospectively, we reviewed reports of all patients admitted to Alberta Health Services/Covenant Health acute-care and acute-/tertiary-care rehabilitation facilities who met inclusion criteria: (1) positive blood culture identified with MRSA or VRE; (2) new episode for the patient; and (3) positive result occurred on or after calendar day 3 of admission. Data are presented as quarterly rates. Screening practices for MRSA and VRE were standardized provincially in October 2015 to include screening for MRSA on admission for patients who had an inpatient admission, received hemodialysis, or was an inmate in a correctional facility in the past 6 months. We also screened for VRE patients admitted to a solid-organ transplant unit or a hematology unit, regardless of risk factors. Results: We detected no changes in the quarterly rates of HA-BSI with MRSA or VRE after admission screening was standardized. Prior to standardized screening, MRSA BSI rates ranged from 0.12 to 0.25 per 10,000 patient days, with an overall rate of 0.18 per 10,000 patient days. After standardization, rates ranged from 0.09 to 0.30 per 10,000 patient days, with an overall rate of 0.17 per 10,000 patient days (P = .46). VRE BSI rates prior to standardization ranged from 0.03 to 0.13 per 10,000 patient days, with an overall rate of 0.08 per 10,000 patient days, which increased slightly to 0.09 per 10,000 patient days after standardized screening, ranging between 0.04 and 0.16 per 10,000 patient days (P = .61). Conclusions: Following the implementation of standardized admission screening and the early initiation of contact precautions, no significant changes were observed in rates of either HA-BSI with MRSA or VRE. Further investigation is required to identify the most effective strategies to reduce HA-BSIs caused by MRSA and VRE.

Funding: None

Disclosures: None

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: None

Disclosures: None

Background: Antibiotic-resistant organisms (AROs) are associated with greater disease severity and poor outcomes. Previous studies have investigated AROs and healthcare-associated infections (HAIs) within larger urban acute-care settings, but similar data for rural settings are scarce. In this stud, we aimed to fill this gap. Methods: Data on antimicrobial resistance (AMR), additional precautions and HAI were collected from 8 rural Alberta acute-care facilities over a 24-hour period from February 4–28, 2019. Data were gathered as part of the national Canadian, Rural, and Northern Acute Care Point Prevalence (CNAPP) survey. All inpatients on included units were reviewed. CNAPP protocol surveillance definitions were used. Results: In total, 961 patients were surveyed, of whom 94 of 961 (9.8%) were on additional precautions. Contact precautions only were most common (54 of 94, 57.4%) and were predominantly in place for MRSA (30 of 94, 31.9%). Of 961 patients, 100 (~10%) met the surveillance definitions for any infection. The most common infections were skin and soft-tissue infections (29 of 100, 29.0%) and bloodstream infections (28 of 100, 28.0%). An HAI occurred in 30 of 961 patients (3.1%); the most common HAIs were surgical site infections (8 of 30, 26.7%) and urinary tract infections (8 of 30, 26.7%). An antimicrobial was prescribed to 333 of 961 patients (34.6%) at the time of the survey, with ceftriaxone the most commonly prescribed (68 of 333, 20.4%). Most patients receiving an antimicrobial (237 of 333, 71.2%) did not meet the surveillance definition for any infection. The most common reason for any antimicrobial administration was empiric therapy (167 of 333, 50.1%). Conclusions: Investigations into antimicrobial use and the burden of HAIs in rural acute-care settings have been limited. In this study, we (1) established provincial baseline data for burden of disease in these facilities due to HAIs and (2) demonstrated that antimicrobial use is common, though most patients who were prescribed an antimicrobial did not meet study definitions for infection. It will be important to continue this type of surveillance in this understudied population to monitor the burden of HAIs over time, to establish antimicrobial utilization trends, and to continue to identify potential antimicrobial stewardship initiatives.

Funding: None

Disclosures: None

Background: Effective medical device reprocessing (MDR) is essential in preventing the spread of microorganisms and maintaining patient safety. Alberta Health Services (AHS) is an Alberta-wide, integrated health system, responsible for delivering health services to >4.3 million people living in the province. In 2010, periodic province-wide MDR reviews were initiated by the provincial health system to verify that the cleaning, disinfection, and sterilization of reusable critical and semicritical medical devices met established standards. To date, there have been 3 review cycles; in cycle 3, a follow-up process for tracking and reporting corrective actions was initiated. Methods: As in previous MDR review cycles, cycle 3 included the use of a standardized suite of tools to measure compliance with standards set by Accreditation Canada, the Canadian Standards Association, and the Government of Alberta. Each cycle involved a review of MDR areas completed by trained reviewers. Interrater reliability among reviewers was maintained through training and debriefings following reviews to ensure agreement. Following reviews, reports were generated for areas, zones, and AHS. As part of the corrective actions and follow-up process, identified deficiencies were categorized into 5 themes. Corrective actions were tracked and periodic reports were generated showing the progress of deficiency resolution. Resolution rates (number of resolved deficiencies divided by total number of of deficiencies) were calculated for each of the identified themes as well as overall for cycle 3. Results: Overall compliance for cycle 3 was 93%. Cycle 3 reviews revealed that more than half of the deficiencies (58%) were identified previously in cycle 2. The resolution rates ranged from 78% to 95% for identified deficiencies for 4 of the 5 themes: documentation, technique, PPE/attire/hand hygiene, and other. The theme related to physical infrastructure showed a considerably lower resolution rate of 49%. The corrective action follow-up process showed increased overall resolution rate from 59% at the start of the follow-up process to 82% at its completion. When this resolution rate was applied to the initial survey compliance rate for cycle 3, overall compliance increased to 99%. Conclusions: Monitoring quality of MDR practices is essential in maintaining and improving patient safety. The standardized provincial review process identified common themes and a coordinated approach to support the resolution of many identified deficiencies. Most of those deficiencies were resolved; however, those deficiencies related to physical infrastructure of the MDR department continue to be seen across review cycles. This review process with follow up of these deficiencies can help bring attention to organization leadership and Funding: authorities during budget cycles.

Funding: None

Disclosures: None

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: Award

Disclosures: None

Background: In Alberta, Canada, surgical site infections (SSIs) following total hip and knee replacements (THRs and TKRs) are reported using the infection prevention and control (IPC) surveillance system, which surveys all THRs and TKRs using the NHSN definitions; and the National Surgical Quality Improvement Program (NSQIP), which uses different definitions and sampling strategies. Deterministic matching of patient data from these sources was used to examine the overlap and discrepancies in SSI reporting. Methods: A retrospective multisite cohort study of IPC and NSQIP superficial, deep, and organ-space THR/TKR SSI data collected 30 days postoperatively from September 1, 2015, to March 31, 2018 was undertaken. To identify patients with procedures captured by both IPC and NSQIP, data were cleaned, duplicates removed, and patients matched 1:1 using year of birth, procedure facility, type, side, date, and time. Positive and negative agreement were assessed, and the Cohen κ values were calculated. The definitions and data capture methods used by both IPC and NSQIP were also compared. Results: There were 7,549 IPC and 2,037 NSQIP patients, respectively, with 1,798 matched patients: IPC (23.8%) and NSQIP (88.3%). Moreover, 17 SSIs were identified by both IPC and NSQIP, including 9 superficial and 8 complex by IPC and 6 superficial and 11 complex by NSQIP. Also, 7 SSIs were identified only by IPC, of which 5 were superficial, and 36 SSIs were identified only by NSQIP, of which 28 were superficial (positive agreement, 0.44; negative agreement, 0.99; κ = .43). Excluding superficial SSIs, 7 SSIs were identified by both IPC and NSQIP; 3 were identified only by IPC; and 12 were identified only by NSQIP (positive agreement, 0.48; negative agreement, 1.00; κ = 0.48). Conclusions: THR/TKR SSI rates reported by IPC and NSQIP were not comparable in this matched dataset. NSQIP identifies more superficial SSIs. Variations in data capture methods and definitions accounted for most of the discordance. Both surveillance systems are critically involved with improving patient outcomes following surgery. However, stakeholders need to be aware of these variations, and education should be provided to facilitate an understanding of the differences and their interpretation. Future work should explore other surgical procedures and larger data sets.

Funding: None

Disclosures: None

Background: The AIBL study, which commenced in November 2006, is a two-center prospective study of a cohort of 1112 volunteers aged 60+. The cohort includes 211 patients meeting NINCDS-ADRDA criteria for Alzheimer's disease (AD) (180 probable and 31 possible). We aimed to identify factors associated with rapid cognitive decline over 18 months in this cohort of AD patients.

Methods: We defined rapid cognitive decline as a drop of 6 points or more on the Mini-Mental State Examination (MMSE) between baseline and 18-month follow-up. Analyses were also conducted with a threshold of 4, 5, 7 and 8 points, as well as with and without subjects who had died or were too severely affected to be interviewed at 18 months and after, both including and excluding subjects whose AD diagnosis was “possible” AD. We sought correlations between rapid cognitive decline and demographic, clinical and biological variables.

Results: Of the 211 AD patients recruited at baseline, we had available data for 156 (73.9%) patients at 18 months. Fifty-one patients were considered rapid cognitive decliners (32.7%). A higher Clinical Dementia Rating scale (CDR) and higher CDR “sum of boxes” score at baseline were the major predictors of rapid cognitive decline in this population. Furthermore, using logistic regression model analysis, patients treated with a cholinesterase inhibitor (CheI) had a higher risk of being rapid cognitive decliners, as did males and those of younger age.

Conclusions: Almost one third of patients satisfying established research criteria for AD experienced rapid cognitive decline. Worse baseline functional and cognitive status and treatment with a CheI were the major factors associated with rapid cognitive decline over 18 months in this population.