Browsing by Author "Larios, Oscar E."

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    Implementation strategies for hospital-based probiotic administration in a stepped-wedge cluster randomized trial design for preventing hospital-acquired Clostridioides difficile infection
    (2023-12-11) Bresee, Lauren C.; Lamont, Nicole; Ocampo, Wrechelle; Holroyd-Leduc, Jayna; Sabuda, Deana; Leal, Jenine; Dalton, Bruce; Kaufman, Jaime; Missaghi, Bayan; Kim, Joseph; Larios, Oscar E.; Henderson, Elizabeth; Raman, Maitreyi; Fletcher, Jared R.; Faris, Peter; Kraft, Scott; Shen, Ye; Louie, Thomas; Conly, John M.
    Abstract Background Clostridioides difficile infection (CDI) is associated with considerable morbidity and mortality in hospitalized patients, especially among older adults. Probiotics have been evaluated to prevent hospital-acquired (HA) CDI in patients who are receiving systemic antibiotics, but the implementation of timely probiotic administration remains a challenge. We evaluated methods for effective probiotic implementation across a large health region as part of a study to assess the real-world effectiveness of a probiotic to prevent HA-CDI (Prevent CDI-55 +). Methods We used a stepped-wedge cluster-randomized controlled trial across four acute-care adult hospitals (n = 2,490 beds) to implement the use of the probiotic Bio-K + ® (Lactobacillus acidophilus CL1285®, L. casei LBC80R® and L. rhamnosus CLR2®; Laval, Quebec, Canada) in patients 55 years and older receiving systemic antimicrobials. The multifaceted probiotic implementation strategy included electronic clinical decision support, local site champions, and both health care provider and patient educational interventions. Focus groups were conducted during study implementation to identify ongoing barriers and facilitators to probiotic implementation, guiding needed adaptations of the implementation strategy. Focus groups were thematically analyzed using the Theoretical Domains Framework and the Consolidated Framework of Implementation Research. Results A total of 340 education sessions with over 1,800 key partners and participants occurred before and during implementation in each of the four hospitals. Site champions were identified for each included hospital, and both electronic clinical decision support and printed educational resources were available to health care providers and patients. A total of 15 individuals participated in 2 focus group and 7 interviews. Key barriers identified from the focus groups resulted in adaptation of the electronic clinical decision support and the addition of nursing education related to probiotic administration. As a result of modifying implementation strategies for identified behaviour change barriers, probiotic adherence rates were from 66.7 to 75.8% at 72 h of starting antibiotic therapy across the four participating acute care hospitals. Conclusions Use of a barrier-targeted multifaceted approach, including electronic clinical decision support, education, focus groups to guide the adaptation of the implementation plan, and local site champions, resulted in a high probiotic adherence rate in the Prevent CDI-55 + study.
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    The economic burden of cardiac implantable electronic device infections in Alberta, Canada: a population-based study using validated administrative data
    (2023-12-05) Rennert-May, Elissa; Chew, Derek; Cannon, Kristine; Zhang, Zuying; Smith, Stephanie; King, Teagan; Exner, Derek V.; Larios, Oscar E.; Leal, Jenine
    Abstract Background Cardiac implantable electronic devices (CIED) are being inserted with increasing frequency. Severe surgical site infections (SSI) that occur after device implantation substantially impact patient morbidity and mortality and can result in multiple hospital admissions and repeat surgeries. It is important to understand the costs associated with these infections as well as healthcare utilization. Therefore, we conducted a population-based study in the province of Alberta, Canada to understand the economic burden of these infections. Methods A cohort of adult patients in Alberta who had CIEDs inserted or generators replaced between January 1, 2011 and December 31, 2019 was used. A validated algorithm of International Classification of Diseases (ICD) codes to identify complex (deep/organ space) SSIs that occurred within the subsequent year was applied to the cohort. The overall mean 12-month inpatient and outpatient costs for the infection and non-infection groups were assessed. In order to control for variables that may influence costs, propensity score matching was completed and incremental costs between those with and without infection were calculated. As secondary outcomes, number of outpatient visits, hospitalizations and length of stay were assessed. Results There were 26,049 procedures performed during our study period, of which 320 (1.23%) resulted in SSIs. In both unadjusted costs and propensity score matched costs the infection group was associated with increased costs. Overall mean cost was $145,312 in the infection group versus $34,264 in the non-infection group. The incremental difference in those with infection versus those without in the propensity score match was $90,620 (Standard deviation $190,185). Approximately 70% of costs were driven by inpatient hospitalizations. Inpatients hospitalizations, length of stay and outpatient visits were all increased in the infection group. Conclusions CIED infections are associated with increased costs and are a burden to the healthcare system. This highlights a need to recognize increasing SSI rates and implement measures to minimize infection risk. Further studies should endeavor to apply this work to full economic evaluations to better understand and identify cost-effective infection mitigation strategies.
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    Validating administrative data to identify complex surgical site infections following cardiac implantable electronic device implantation: a comparison of traditional methods and machine learning
    (2022-11-10) Rennert-May, Elissa; Leal, Jenine; MacDonald, Matthew K.; Cannon, Kristine; Smith, Stephanie; Exner, Derek; Larios, Oscar E.; Bush, Kathryn; Chew, Derek
    Abstract Background Cardiac implantable electronic device (CIED) surgical site infections (SSIs) have been outpacing the increases in implantation of these devices. While traditional surveillance of these SSIs by infection prevention and control would likely be the most accurate, this is not practical in many centers where resources are constrained. Therefore, we explored the validity of administrative data at identifying these SSIs. Methods We used a cohort of all patients with CIED implantation in Calgary, Alberta where traditional surveillance was done for infections from Jan 1, 2013 to December 31, 2019. We used this infection subgroup as our “gold standard” and then utilized various combinations of administrative data to determine which best optimized the sensitivity and specificity at identifying infection. We evaluated six approaches to identifying CIED infection using administrative data, which included four algorithms using International Classification of Diseases codes and/or Canadian Classification of Health Intervention codes, and two machine learning models. A secondary objective of our study was to assess if machine learning techniques with training of logistic regression models would outperform our pre-selected codes. Results We determined that all of the pre-selected algorithms performed well at identifying CIED infections but the machine learning model was able to produce the optimal method of identification with an area under the receiver operating characteristic curve (AUC) of 96.8%. The best performing pre-selected algorithm yielded an AUC of 94.6%. Conclusions Our findings suggest that administrative data can be used to effectively identify CIED infections. While machine learning performed the most optimally, in centers with limited analytic capabilities a simpler algorithm of pre-selected codes also has excellent yield. This can be valuable for centers without traditional surveillance to follow trends in SSIs over time and identify when rates of infection are increasing. This can lead to enhanced interventions for prevention of SSIs.